# Awesome Dataviz: full directory > The open directory of data visualization tools. 291 tools, data refreshed 2026-10-04. Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## JavaScript charting libraries > Libraries for line, bar, area, pie, scatter and other standard charts in the browser. 29 tools, ranked by GitHub stars. Libraries for drawing standard charts (line, bar, area, pie, scatter and more) in the browser. They differ mostly in rendering technology, in how charts are configured, and in licensing. SVG output is easy to style, inspect and make accessible; Canvas and WebGL renderers scale to far more data points. Start with data size and interactivity: SVG libraries are comfortable up to a few thousand marks, while Canvas-based libraries such as Chart.js and Apache ECharts handle much larger series. Then compare configuration style (declarative options objects versus code), framework wrappers, accessibility support and whether the license fits your product. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [Chart.js](https://awesomedataviz.com/tools/chart-js/) | 67,733 | 21 | MIT | Charts with the canvas tag. | | 2 | [Apache ECharts](https://awesomedataviz.com/tools/echarts/) | 67,449 | 266 | Apache-2.0 | Highly customizable and interactive charts ready for big datasets. | | 3 | [Plotly.js](https://awesomedataviz.com/tools/plotly-js/) | 18,355 | 1,549 | MIT | Powerful declarative library with support for 20 chart types. | | 4 | [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/) | 17,473 | 329 | Apache-2.0 | Performant HTML5 canvas financial charts, from TradingView. | | 5 | [ApexCharts](https://awesomedataviz.com/tools/apexcharts/) | 15,169 | 832 | Other | Modern & Interactive SVG Charts. | | 6 | [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/) | 15,088 | 0 | MIT | Simple, responsive SVG charts with zero dependencies. | | 7 | [Chartist.js](https://awesomedataviz.com/tools/chartist-js/) | 13,390 | 1 | MIT | Responsive charts with great browser compatibility. | | 8 | [G2](https://awesomedataviz.com/tools/g2/) | 12,631 | 88 | MIT | An interactive and responsive charting library based on the grammar of graphics, maintained by Alibaba. | | 9 | [uPlot](https://awesomedataviz.com/tools/uplot/) | 10,542 | 118 | MIT | Small, fast canvas-based charts for time series, lines, areas, OHLC and bars. | | 10 | [C3.js](https://awesomedataviz.com/tools/c3-js/) | 9,350 | 18 | MIT | D3-based reusable chart library. | | 11 | [dc.js](https://awesomedataviz.com/tools/dc-js/) | 7,430 | 0 | Apache-2.0 | Multi-dimensional charting built to work natively with crossfilter. | | 12 | [MetricsGraphics.js](https://awesomedataviz.com/tools/metricsgraphics-js/) | 7,394 | 0 | MPL-2.0 | Optimized for time-series data. | | 13 | [NVD3](https://awesomedataviz.com/tools/nvd3/) | 7,229 | 0 | Apache-2.0 | A reusable charting library written in d3.js. | | 14 | [roughViz](https://awesomedataviz.com/tools/roughviz/) | 7,161 | 0 | MIT | Sketchy, hand-drawn style charts for the browser, based on Rough.js. | | 15 | [Charts.css](https://awesomedataviz.com/tools/charts-css/) | 6,582 | 0 | MIT | CSS framework that styles HTML tables as charts. | | 16 | [Frappe Gantt](https://awesomedataviz.com/tools/frappe-gantt/) | 6,134 | 38 | MIT | Simple, interactive SVG Gantt chart library. | | 17 | [billboard.js](https://awesomedataviz.com/tools/billboard-js/) | 6,014 | 138 | MIT | Reusable D3.js-based chart library with SVG and Canvas rendering, maintained by NAVER. | | 18 | [Observable Plot](https://awesomedataviz.com/tools/observable-plot/) | 5,400 | 38 | ISC | A JavaScript library for exploratory data visualization. | | 19 | [TOAST UI Chart](https://awesomedataviz.com/tools/toast-ui-chart/) | 5,400 | 0 | MIT | Complete library with support for legacy browsers. | | 20 | [Epoch](https://awesomedataviz.com/tools/epoch/) | 4,942 | 0 | MIT | Perfect to create real-time charts. | | 21 | [Dygraphs](https://awesomedataviz.com/tools/dygraphs/) | 3,243 | 54 | MIT | Interactive line charts library that works with huge datasets. | | 22 | [Unovis](https://awesomedataviz.com/tools/unovis/) | 2,857 | 590 | Apache-2.0 | Modular data visualization framework for React, Angular, Svelte, Vue and vanilla TypeScript, by F5. | | 23 | [TechanJS](https://awesomedataviz.com/tools/techanjs/) | 2,436 | 0 | MIT | Stock and financial charts. | | 24 | [Vizzu](https://awesomedataviz.com/tools/vizzu/) | 2,036 | 21 | Apache-2.0 | Library for animated data visualizations and data stories. | | 25 | [GraphicsJS](https://awesomedataviz.com/tools/graphicsjs/) | 995 | 0 | BSD-3-Clause | Lightweight JS graphics library with intuitive API, based on SVG/VML. | | 26 | [dxcharts-lite](https://awesomedataviz.com/tools/dxcharts-lite/) | 101 | 3,699 | MPL-2.0 | Flexible financial charting library based on HTML5 canvas. | | 27 | [lit-line](https://awesomedataviz.com/tools/lit-line/) | 22 | 0 | MIT | SVG Line Chart Web Component - light, fast, interactive & fully responsive. | | 28 | [Glyph](https://awesomedataviz.com/tools/glyph/) | 3 | 258 | Apache-2.0 | Deterministic chart library that renders the same JSON spec to identical SVG on every platform, with DuckDB inside and an MCP server for AI agents. | | 29 | [Google Charts](https://awesomedataviz.com/tools/google-charts/) | – | – | – | Interactive charts for browsers and mobile devices. | Source: https://awesomedataviz.com/categories/javascript-charting-libraries/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## JavaScript graph & network visualization libraries > Node-link diagrams for networks, dependency graphs and knowledge graphs. 15 tools, ranked by GitHub stars. Libraries for drawing node-link diagrams: social networks, dependency graphs, knowledge graphs, flowcharts and other relational data. Most pair a renderer with layout algorithms (force-directed, hierarchical, circular) and interactions such as dragging, zooming and selecting nodes. Graph size decides a lot: Sigma.js renders with WebGL to keep large graphs interactive, Cytoscape.js combines visualization with graph analysis, and diagramming libraries focus on editing and constraint-based layout. For the graph data model and algorithms on their own, see Graphology. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [xyflow](https://awesomedataviz.com/tools/xyflow/) | 38,582 | 510 | MIT | React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. | | 2 | [G6](https://awesomedataviz.com/tools/g6/) | 12,323 | 44 | MIT | Graph visualization library powered by Javascript & Typescript, maintained by Alibaba | | 3 | [Sigma.js](https://awesomedataviz.com/tools/sigma-js/) | 12,180 | 6 | MIT | JavaScript library dedicated to graph drawing. | | 4 | [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/) | 11,232 | 185 | MIT | JavaScript library for graph drawing maintained by Cytoscape core developers. | | 5 | [Vue Flow](https://awesomedataviz.com/tools/vue-flow/) | 6,888 | 22 | MIT | Flowchart and node-based graph component for Vue 3. | | 6 | [X6](https://awesomedataviz.com/tools/x6/) | 6,716 | 116 | MIT | Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. | | 7 | [3d-force-graph](https://awesomedataviz.com/tools/3d-force-graph/) | 6,433 | 9 | MIT | 3D force-directed graph component using Three.js/WebGL. | | 8 | [dagre](https://awesomedataviz.com/tools/dagre/) | 5,814 | 110 | MIT | Directed graph layout library for JavaScript. | | 9 | [JointJS](https://awesomedataviz.com/tools/jointjs/) | 5,393 | 151 | MPL-2.0 | SVG-based JavaScript diagramming library for interactive diagrams and graph editors. | | 10 | [VivaGraph](https://awesomedataviz.com/tools/vivagraph/) | 3,862 | 1 | BSD-3-Clause | Graph drawing library for JavaScript. | | 11 | [elkjs](https://awesomedataviz.com/tools/elkjs/) | 2,801 | 61 | EPL-2.0 OR GPL-3.0-or-later | Eclipse Layout Kernel (ELK) graph layout algorithms for JavaScript. | | 12 | [Uber React Digraph](https://awesomedataviz.com/tools/uber-react-digraph/) | 2,644 | 0 | MIT | React.js based directed graph library maintained by UBER. | | 13 | [Cola.js](https://awesomedataviz.com/tools/cola-js/) | 2,098 | 3 | MIT | A tool to create diagrams using constraint-based optimization techniques. Works with d3 and svg.js. | | 14 | [diagram.js](https://awesomedataviz.com/tools/diagram-js/) | 1,926 | 268 | MIT | Javascript diagram library serving as the basis for camunda's online BPMN modeler. | | 15 | [Vizdom](https://awesomedataviz.com/tools/vizdom/) | 193 | 0 | Apache-2.0 | A declarative graph layout and rendering engine for Javascript/Typescript powered by Rust/WebAssembly. | Source: https://awesomedataviz.com/categories/javascript-graph-visualization/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## JavaScript map & geospatial visualization libraries > Interactive web maps, globes and GPU-rendered geospatial layers. 19 tools, ranked by GitHub stars. Libraries for interactive web maps and geospatial visualization, from tiled slippy maps with markers to GPU-rendered layers with millions of points, 3D globes and choropleths. Leaflet is the lightweight standard for 2D tiled maps. Deck.gl and L7 render large geospatial datasets with WebGL, and Cesium focuses on 3D globes and terrain. For a choropleth of countries or regions, an SVG map such as DataMaps may be all you need. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [Leaflet](https://awesomedataviz.com/tools/leaflet/) | 45,702 | 184 | BSD-2-Clause | JavaScript library for mobile-friendly interactive maps. | | 2 | [Cesium](https://awesomedataviz.com/tools/cesium/) | 15,798 | 3,159 | Apache-2.0 | WebGL 3D globes and maps. | | 3 | [Deck.gl](https://awesomedataviz.com/tools/deck-gl/) | 14,623 | 418 | MIT | WebGL framework for visual exploratory data analysis of large datasets. | | 4 | [OpenLayers](https://awesomedataviz.com/tools/openlayers/) | 12,602 | 827 | BSD-2-Clause | Library for interactive web maps with support for many data sources, formats and projections. | | 5 | [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/) | 11,801 | 1,416 | BSD-3-Clause | WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. | | 6 | [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/) | 8,503 | 20 | MIT | React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. | | 7 | [Potree](https://awesomedataviz.com/tools/potree/) | 5,628 | 1 | Other | WebGL point cloud viewer for large datasets such as LiDAR scans. | | 8 | [maptalks.js](https://awesomedataviz.com/tools/maptalks-js/) | 4,534 | 293 | BSD-3-Clause | Pluggable JavaScript library for integrated 2D/3D maps. | | 9 | [L7](https://awesomedataviz.com/tools/l7/) | 4,070 | 112 | MIT | Large-scale WebGL-powered Geospatial Data Visualization analysis framework, maintained by Alibaba | | 10 | [DataMaps](https://awesomedataviz.com/tools/datamaps/) | 3,797 | 1 | MIT | Interactive SVG maps using D3.js. | | 11 | [React Simple Maps](https://awesomedataviz.com/tools/react-simple-maps/) | 3,379 | 18 | MIT | Composable SVG map charts for React, based on d3-geo and TopoJSON. | | 12 | [globe.gl](https://awesomedataviz.com/tools/globe-gl/) | 3,190 | 20 | MIT | UI component for globe data visualization using Three.js/WebGL. | | 13 | [Mapael](https://awesomedataviz.com/tools/mapael/) | 1,007 | 0 | MIT | JQuery plugin based on raphael.js to display vector maps. | | 14 | [Pharos AI](https://awesomedataviz.com/tools/pharos-ai/) | 182 | 477 | AGPL-3.0 | Open-source OSINT conflict-tracking dashboard with geospatial visualization using Deck.gl, MapLibre, and React. (Source Code) | | 15 | [L7 Plot](https://awesomedataviz.com/tools/l7-plot/) | 91 | 0 | MIT | Geospatial Visualization Chart Library, maintained by Alibaba | | 16 | [Dipper](https://awesomedataviz.com/tools/dipper/) | 29 | 0 | MIT | Map application development framework powered by L7, maintained by Alibaba. | | 17 | [VectorAtlas](https://awesomedataviz.com/tools/vectoratlas/) | 5 | 11 | CC-BY-4.0 | Free, 80KB SVG world map with one path per country, id-keyed by ISO 3166-1 alpha-2 code, ready for choropleths. | | 18 | [Globedots](https://awesomedataviz.com/tools/globedots/) | 1 | 33 | MIT | Dot-matrix WebGL2 globe in 17 kB with markers, arcs, labels, heat maps, and a day-night line. | | 19 | [CanvasGlobe](https://awesomedataviz.com/tools/canvasglobe/) | 0 | 109 | Other | Interactive Canvas 2D globes and flat world maps for JavaScript and React. | Source: https://awesomedataviz.com/categories/javascript-maps/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## D3.js > The low-level toolkit behind many web visualizations. 1 tool, ranked by GitHub stars. D3 (Data-Driven Documents) is the low-level JavaScript toolkit behind many of the libraries in this directory. Instead of chart types it provides modules for scales, shapes, layouts, transitions and data joins, so any visualization can be built from primitives. D3 has an ecosystem of its own: for plugins, examples and learning material, see the dedicated Awesome D3 list. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [D3.js](https://awesomedataviz.com/tools/d3/) | 113,802 | 2 | ISC | JavaScript library for producing dynamic, data-driven visualizations with SVG, Canvas and HTML. | Source: https://awesomedataviz.com/categories/d3/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## React chart & visualization libraries > Chart components that compose with React state and props. 15 tools, ranked by GitHub stars. Chart and visualization components built for React. Charts are components configured with props, so they compose with application state and re-render predictably; under the hood most build on D3, SVG or Canvas. Compare the API level first: high-level chart components such as Recharts and nivo get a dashboard running quickly, while lower-level primitives give full control over the design. Then check server-side rendering support, bundle size and TypeScript types. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [Recharts](https://awesomedataviz.com/tools/recharts/) | 27,612 | 1,046 | MIT | Declarative react components to render D3 charts. | | 2 | [visx](https://awesomedataviz.com/tools/visx/) | 21,075 | 121 | MIT | Low-level visualization components that combine D3 with React, by Airbnb. | | 3 | [Tremor](https://awesomedataviz.com/tools/tremor/) | 16,485 | 0 | Apache-2.0 | React components for building charts and dashboards, based on Recharts and Tailwind CSS. | | 4 | [nivo](https://awesomedataviz.com/tools/nivo/) | 14,106 | 24 | MIT | Supercharged dataviz components for React with isomorphic ability, demo. | | 5 | [Victory](https://awesomedataviz.com/tools/victory/) | 11,238 | 3 | MIT | Composable components for building interactive data visualizations | | 6 | [React-vis](https://awesomedataviz.com/tools/react-vis/) | 8,785 | 0 | MIT | React components to build data visualizations. | | 7 | [react-chartjs-2](https://awesomedataviz.com/tools/react-chartjs-2/) | 6,939 | 44 | MIT | React components for Chart.js. | | 8 | [BizCharts](https://awesomedataviz.com/tools/bizcharts/) | 6,189 | 0 | MIT | Data visualization library based on G2 and React. | | 9 | [MUI X Charts](https://awesomedataviz.com/tools/mui-x-charts/) | 5,859 | 2,335 | MIT | React chart components from MUI; the community package is MIT-licensed. | | 10 | [echarts-for-react](https://awesomedataviz.com/tools/echarts-for-react/) | 5,006 | 4 | MIT | React wrapper for Apache ECharts. | | 11 | [Graphic Walker](https://awesomedataviz.com/tools/graphic-walker/) | 3,257 | 51 | Apache-2.0 | An embeddable React component that functions as an open source alternative to Tableau, which allows data scientists to analyze data and visualize patterns with simple drag-and-drop operations. | | 12 | [Semiotic](https://awesomedataviz.com/tools/semiotic/) | 2,710 | 2,547 | Apache-2.0 | React data visualization library for charts, network graphs and streaming data. | | 13 | [DevExtreme React Chart](https://awesomedataviz.com/tools/devextreme-react-chart/) | 2,068 | 1 | Other | High-performance plugin-based React chart for Bootstrap and Material Design. | | 14 | [Graphin](https://awesomedataviz.com/tools/graphin/) | 1,098 | 2 | MIT | Graph visualization library powered by React & Typescript (built on top of G6), maintained by Alibaba. | | 15 | [React Svg Textures](https://awesomedataviz.com/tools/react-svg-textures/) | 32 | 0 | MIT | Textures.js ported to React. Fully isomorphic. | Source: https://awesomedataviz.com/categories/react/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## React Native chart libraries > Charts for React Native apps on iOS and Android. 5 tools, ranked by GitHub stars. Chart libraries for React Native apps on iOS and Android. React Native renders native views rather than browser DOM, so most web chart libraries do not work directly; these libraries draw with SVG, Canvas or native graphics instead. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [react-native-maps](https://awesomedataviz.com/tools/react-native-maps/) | 16,004 | 66 | MIT | Map view component for iOS and Android in React Native. | | 2 | [F2](https://awesomedataviz.com/tools/f2/) | 7,997 | 28 | MIT | An elegant, interactive and flexible charting library for mobile, maintained by Alibaba | | 3 | [React Native Chart Kit](https://awesomedataviz.com/tools/react-native-chart-kit/) | 3,112 | 131 | MIT | Line, bar, pie, progress and contribution graph charts for React Native. | | 4 | [react-native-graph](https://awesomedataviz.com/tools/react-native-graph/) | 2,627 | 20 | MIT | Animated, high-performance line graphs for React Native, built with Skia. | | 5 | [Victory Native](https://awesomedataviz.com/tools/victory-native/) | 1,232 | 29 | MIT | High-performance charting library for React Native, built on React Native Skia. | Source: https://awesomedataviz.com/categories/react-native/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## More JavaScript visualization libraries > Visualization grammars, timelines, textures and other web tools. 17 tools, ranked by GitHub stars. Visualization grammars, timeline and pattern libraries, and other JavaScript tools that do not fit a single chart category. Vega and Vega-Lite describe charts as JSON specifications that can be rendered, saved and shared; Timeline.js and Vis.js cover timelines and networks; Textures.js adds SVG patterns to any chart. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/) | 15,775 | 1 | MIT | Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. | | 2 | [Vega](https://awesomedataviz.com/tools/vega/) | 12,008 | 148 | BSD-3-Clause | Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. | | 3 | [Perspective](https://awesomedataviz.com/tools/perspective/) | 11,270 | 337 | Apache-2.0 | Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. | | 4 | [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/) | 10,758 | 805 | MIT | Vue.js component for Apache ECharts. | | 5 | [Textures.js](https://awesomedataviz.com/tools/textures-js/) | 6,088 | 0 | MIT | A library to create SVG patterns. | | 6 | [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/) | 5,718 | 5 | MIT | Vue.js wrapper for Chart.js. | | 7 | [Vega-Lite](https://awesomedataviz.com/tools/vega-lite/) | 5,502 | 120 | BSD-3-Clause | Is a high-level grammar of interactive graphics. It provides a concise JSON syntax for rapidly generating visualizations to support analysis. | | 8 | [ngx-charts](https://awesomedataviz.com/tools/ngx-charts/) | 4,363 | 19 | MIT | Declarative charting framework for Angular, using D3 for math and Angular for rendering. | | 9 | [Vis.js](https://awesomedataviz.com/tools/vis-js/) | 3,632 | 246 | Apache-2.0 | A dynamic visualization library including timeline, networks and graphs (2D and 3D). | | 10 | [Timeline.js](https://awesomedataviz.com/tools/timeline-js/) | 3,224 | 57 | MPL-2.0 | Create interactive timelines. | | 11 | [Piecon](https://awesomedataviz.com/tools/piecon/) | 2,295 | 0 | MIT | Pie charts in your favicon. | | 12 | [Layer Cake](https://awesomedataviz.com/tools/layer-cake/) | 1,793 | 67 | MIT | Graphics framework for building reusable charts with Svelte. | | 13 | [Graphology](https://awesomedataviz.com/tools/graphology/) | 1,756 | 10 | MIT | A robust & multipurpose Graph object for javascript & TypeScript; Serves as a base library to power other graph visualization libraries. | | 14 | [vtk.js](https://awesomedataviz.com/tools/vtk-js/) | 1,536 | 361 | BSD-3-Clause | JavaScript implementation of the Visualization Toolkit (VTK) for scientific visualization on the web. | | 15 | [Mosaic](https://awesomedataviz.com/tools/mosaic/) | 1,390 | 278 | BSD-3-Clause | Framework for linking databases such as DuckDB with interactive views to visualize large datasets. | | 16 | [gp-treemap](https://awesomedataviz.com/tools/gp-treemap/) | 10 | 184 | GPL-2.0 | Open source HTML canvas treemap component supporting millions of nodes, and some functional resource usage tools, like disk and S3 usage visualization (GrandPerspective-style) | | 17 | [ODataMap](https://awesomedataviz.com/tools/odatamap/) | 10 | 20 | MIT | Interactive scientific research data map. Visualizes 250M+ papers across 7 knowledge continents using D3.js. Demo | Source: https://awesomedataviz.com/categories/javascript-visualization-tools/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Android chart libraries > Native chart views for Android apps in Java and Kotlin. 5 tools, ranked by GitHub stars. Native chart libraries for Android apps, written in Java or Kotlin. They draw with Android graphics APIs, support touch gestures such as pinch-zoom and dragging, and are added to a project as Gradle dependencies. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [MPAndroidChart](https://awesomedataviz.com/tools/mpandroidchart/) | 38,183 | 20 | Apache-2.0 | A powerful & easy to use chart library. | | 2 | [HelloCharts](https://awesomedataviz.com/tools/hellocharts/) | 7,559 | 0 | Apache-2.0 | Android chart library with line, column, pie, bubble and combo charts, plus zoom and scroll. | | 3 | [WilliamChart](https://awesomedataviz.com/tools/williamchart/) | 5,095 | 2 | – | Simple chart library. | | 4 | [Vico](https://awesomedataviz.com/tools/vico/) | 3,185 | 521 | Apache-2.0 | Extensible chart library for Jetpack Compose and Compose Multiplatform. | | 5 | [DecoView](https://awesomedataviz.com/tools/decoview/) | 984 | 0 | Apache-2.0 | Animated circular wheel chart library. | Source: https://awesomedataviz.com/categories/android/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## C++ visualization libraries & applications > Scientific, 3D and high-performance visualization. 14 tools, ranked by GitHub stars. Libraries and applications for scientific, 3D and high-performance visualization in C++. Many build on VTK, the Visualization Toolkit, which also powers ParaView. Most of these projects ship Python bindings, so they are often used from Python too. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [ImPlot](https://awesomedataviz.com/tools/implot/) | 6,239 | 104 | MIT | Immediate-mode plotting library for Dear ImGui. | | 2 | [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/) | 6,230 | 615 | MPL-2.0 | Open-source Qt5 application to plot charts (based on Qwt). | | 3 | [Matplot++](https://awesomedataviz.com/tools/matplotpp/) | 4,937 | 3 | MIT | C++ graphics library for data visualization with a MATLAB-like API. | | 4 | [F3D](https://awesomedataviz.com/tools/f3d/) | 4,741 | 696 | BSD-3-Clause | Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. | | 5 | [Mapnik](https://awesomedataviz.com/tools/mapnik/) | 3,965 | 191 | LGPL-2.1 | Toolkit for rendering maps, widely used to render OpenStreetMap tiles. | | 6 | [ROOT](https://awesomedataviz.com/tools/root/) | 3,307 | 4,406 | Other | CERN framework for analyzing, storing and visualizing large scientific datasets. | | 7 | [VTK](https://awesomedataviz.com/tools/vtk/) | 3,211 | 5,558 | BSD | Open-source library for 3d Graphics, image processing and visualization. | | 8 | [MapLibre Native](https://awesomedataviz.com/tools/maplibre-native/) | 2,251 | 414 | BSD-2-Clause | Interactive vector tile map rendering for iOS, Android and other native platforms. | | 9 | [Polyscope](https://awesomedataviz.com/tools/polyscope/) | 2,214 | 61 | MIT | Viewer and user interface for 3D geometry processing. | | 10 | [ParaView](https://awesomedataviz.com/tools/paraview/) | 1,704 | 1,916 | BSD-3-Clause | Multi-platform data analysis and visualization application based on VTK. | | 11 | [LargeVis](https://awesomedataviz.com/tools/largevis/) | 711 | 0 | Apache-2.0 | Implementation of the LargeVis paper, used to visualize large-scale and high-dimensional data. | | 12 | [VisIt](https://awesomedataviz.com/tools/visit/) | 532 | 353 | BSD-3-Clause | Visualization and analysis tool for large mesh-based scientific data, developed at LLNL. | | 13 | [TTK](https://awesomedataviz.com/tools/ttk/) | 481 | 480 | BSD-3-Clause | Topological data analysis and visualization. | | 14 | [QCustomPlot](https://awesomedataviz.com/tools/qcustomplot/) | – | – | – | Qt C++ widget for plotting and data visualization. | Source: https://awesomedataviz.com/categories/cpp/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Open-source dashboards & BI tools > Self-hosted business intelligence, monitoring and dashboards. 12 tools, ranked by GitHub stars. Open-source business intelligence and dashboard applications. They connect to databases and data warehouses, let teams explore data with SQL or visual query builders, and publish dashboards that refresh on a schedule, an alternative to commercial BI suites that you can self-host. Monitoring-oriented tools such as Grafana focus on time series from metrics and logs, while BI tools such as Apache Superset and Metabase focus on querying business data. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [Grafana](https://awesomedataviz.com/tools/grafana/) | 77,071 | 11,330 | AGPL-3.0 | Observability and data visualization platform for metrics, logs and traces from many data sources. | | 2 | [Apache Superset](https://awesomedataviz.com/tools/superset/) | 75,035 | 5,646 | Apache-2.0 | Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. | | 3 | [Metabase](https://awesomedataviz.com/tools/metabase/) | 49,536 | 6,704 | Other | Business intelligence tool for querying data and building dashboards, with embedded analytics. | | 4 | [Redash](https://awesomedataviz.com/tools/redash/) | 28,833 | 90 | BSD-2-Clause | Query data sources with SQL, then visualize the results and build dashboards. | | 5 | [Kibana](https://awesomedataviz.com/tools/kibana/) | 21,305 | 21,018 | Other | Visualization and dashboard UI for data stored in Elasticsearch. | | 6 | [Evidence](https://awesomedataviz.com/tools/evidence/) | 6,978 | 204 | MIT | Business intelligence as code: build reports and dashboards with SQL and Markdown. | | 7 | [Lightdash](https://awesomedataviz.com/tools/lightdash/) | 6,174 | 12,219 | Other | BI tool that turns dbt projects into metrics, charts and dashboards. | | 8 | [Observable Framework](https://awesomedataviz.com/tools/observable-framework/) | 3,657 | 12 | ISC | Static site generator for data apps, dashboards and reports using JavaScript, SQL and Markdown. | | 9 | [Rill](https://awesomedataviz.com/tools/rill/) | 2,928 | 1,540 | Apache-2.0 | BI tool for fast, metrics-first dashboards powered by OLAP engines such as DuckDB and ClickHouse. | | 10 | [Perses](https://awesomedataviz.com/tools/perses/) | 2,468 | 592 | Apache-2.0 | CNCF dashboard tool and open dashboard specification for observability data such as Prometheus metrics. | | 11 | [OpenSearch Dashboards](https://awesomedataviz.com/tools/opensearch-dashboards/) | 2,130 | 941 | Apache-2.0 | Visualization and dashboard UI for OpenSearch; Apache-2.0 fork of Kibana 7.10. | | 12 | [DataLens](https://awesomedataviz.com/tools/datalens/) | 1,705 | 32 | Apache-2.0 | Business intelligence and data visualization system, originally developed at Yandex. | Source: https://awesomedataviz.com/categories/dashboards-and-bi/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Flutter chart libraries > Charts for Flutter apps on mobile, web and desktop. 3 tools, ranked by GitHub stars. Chart libraries for Flutter apps written in Dart. Because Flutter draws its own widgets, the same chart renders consistently on iOS, Android, the web and desktop. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [fl_chart](https://awesomedataviz.com/tools/fl-chart/) | 7,583 | 51 | MIT | Customizable Flutter chart library with line, bar, pie, scatter and radar charts. | | 2 | [flutter_map](https://awesomedataviz.com/tools/flutter-map/) | 3,023 | 42 | BSD-3-Clause | Vendor-free, customizable interactive map package for Flutter. | | 3 | [Graphic](https://awesomedataviz.com/tools/graphic/) | 1,792 | 7 | MIT | Grammar of graphics data visualization and charting library for Flutter. | Source: https://awesomedataviz.com/categories/flutter/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Go charting & plotting libraries > Charts, plots and SVG from Go programs. 7 tools, ranked by GitHub stars. Libraries for producing charts from Go programs: static plots for analysis with plot, low-level SVG generation with svgo, and interactive HTML charts based on Apache ECharts with go-echarts. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [termui](https://awesomedataviz.com/tools/termui/) | 13,590 | 0 | MIT | Terminal dashboard and widget library with charts, gauges, sparklines and more. | | 2 | [go-echarts](https://awesomedataviz.com/tools/go-echarts/) | 7,645 | 16 | MIT | Simple yet powerful data visualizing library for Go. | | 3 | [go-diagrams](https://awesomedataviz.com/tools/go-diagrams/) | 5,235 | 0 | MIT | Diagram-as-code library for system architecture diagrams in Go, rendered with Graphviz. | | 4 | [asciigraph](https://awesomedataviz.com/tools/asciigraph/) | 3,099 | 72 | BSD-3-Clause | Lightweight ASCII line graphs for command-line apps. | | 5 | [termdash](https://awesomedataviz.com/tools/termdash/) | 3,041 | 21 | Apache-2.0 | Terminal-based dashboard library with line charts, bar charts, gauges and donuts. | | 6 | [plot](https://awesomedataviz.com/tools/plot/) | 2,969 | 5 | BSD-3-Clause | API for building and drawing plots in Go. | | 7 | [svgo](https://awesomedataviz.com/tools/svgo/) | 2,251 | 0 | Other | Go Language Library for SVG generation. | Source: https://awesomedataviz.com/categories/go/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## iOS & Swift chart libraries > Native charts for iOS and macOS apps. 7 tools, ranked by GitHub stars. Native chart libraries for iOS (and often macOS) apps in Swift and Objective-C. Since iOS 16, Apple ships Swift Charts with the SDK, so third-party libraries are mostly chosen for chart types, customization or support for older OS versions. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [Charts](https://awesomedataviz.com/tools/charts/) | 27,997 | 1 | Apache-2.0 | IOS port of MPAndroidChart. You can create charts for both platforms with very similar code. | | 2 | [PNChart](https://awesomedataviz.com/tools/pnchart/) | 9,634 | 0 | MIT | A simple and beautiful chart lib used in Piner and CoinsMan. | | 3 | [ChartView](https://awesomedataviz.com/tools/chartview/) | 5,646 | 15 | MIT | Line, bar and pie chart views built with SwiftUI. | | 4 | [JBChartView](https://awesomedataviz.com/tools/jbchartview/) | 3,693 | 0 | Other | Charting library for both line and bar graphs. | | 5 | [Core Plot](https://awesomedataviz.com/tools/core-plot/) | 2,758 | 0 | BSD-3-Clause | 2D plotting framework for macOS, iOS and tvOS. | | 6 | [BEMSimpleLineGraph](https://awesomedataviz.com/tools/bemsimplelinegraph/) | 2,627 | 0 | MIT | Highly customizable and interactive line graphs. | | 7 | [SwiftCharts](https://awesomedataviz.com/tools/swiftcharts/) | 2,572 | 0 | Apache-2.0 | Customizable charts library for iOS. | Source: https://awesomedataviz.com/categories/ios/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Julia plotting packages > Plotting for scientific computing in Julia. 4 tools, ranked by GitHub stars. Plotting packages for Julia, a language for scientific computing and data analysis. Makie offers GPU-powered interactive and publication-quality plots, and Plots.jl provides one API over multiple plotting backends. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [Makie](https://awesomedataviz.com/tools/makie/) | 2,816 | 199 | MIT | Interactive, high-performance plotting ecosystem for Julia with OpenGL, WebGL and Cairo backends. | | 2 | [Plots.jl](https://awesomedataviz.com/tools/plots-jl/) | 1,952 | 89 | – | Plotting meta-package for Julia with a single API over multiple backends. | | 3 | [Gadfly.jl](https://awesomedataviz.com/tools/gadfly-jl/) | 1,927 | 0 | Other | Statistical graphics for Julia based on the grammar of graphics. | | 4 | [UnicodePlots.jl](https://awesomedataviz.com/tools/unicodeplots-jl/) | 1,549 | 31 | Other | Unicode-based scientific plotting in the terminal for Julia. | Source: https://awesomedataviz.com/categories/julia/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Java, Kotlin & Scala visualization libraries > Charts for desktop apps, servers and notebooks on the JVM. 4 tools, ranked by GitHub stars. Charting and visualization libraries for Java, Kotlin and Scala, used in desktop applications, server-side chart generation and data science notebooks. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [XChart](https://awesomedataviz.com/tools/xchart/) | 1,596 | 307 | Apache-2.0 | Lightweight Java library for plotting data. | | 2 | [JFreeChart](https://awesomedataviz.com/tools/jfreechart/) | 1,391 | 0 | LGPL-2.1 | 2D chart library for Java applications using Swing, JavaFX or server-side rendering. | | 3 | [Kandy](https://awesomedataviz.com/tools/kandy/) | 746 | 49 | Apache-2.0 | Kotlin plotting library with a typed DSL, developed by JetBrains. | | 4 | [Lets-Plot for Kotlin](https://awesomedataviz.com/tools/lets-plot-for-kotlin/) | 487 | 129 | MIT | Grammar of graphics plotting API for Kotlin, built on Lets-Plot. | Source: https://awesomedataviz.com/categories/jvm/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Machine learning visualization tools > Training metrics, experiment tracking, embeddings and LLM traces. 15 tools, ranked by GitHub stars. Tools for visualizing machine learning work: training metrics and experiment tracking, model debugging, embeddings, and traces of LLM applications. Most are Python packages that log from training or inference code to a local or hosted dashboard. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [Netron](https://awesomedataviz.com/tools/netron/) | 33,544 | 926 | MIT | Viewer for neural network, deep learning and machine learning models. | | 2 | [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/) | 25,009 | 0 | MIT | LaTeX code for drawing neural network architecture diagrams. | | 3 | [Opik](https://awesomedataviz.com/tools/opik/) | 22,373 | 4,323 | Apache-2.0 | Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. | | 4 | [Phoenix](https://awesomedataviz.com/tools/phoenix/) | 11,704 | 3,725 | Elastic-2.0 | ML observability in a notebook with UMAP visualizations | | 5 | [FiftyOne](https://awesomedataviz.com/tools/fiftyone/) | 11,143 | 8,917 | Apache-2.0 | Tool for visualizing, curating and evaluating computer vision datasets and models. | | 6 | [Visdom](https://awesomedataviz.com/tools/visdom/) | 10,318 | 548 | Apache-2.0 | Tool for real-time visualization and monitoring of live data such as ML experiments. | | 7 | [BertViz](https://awesomedataviz.com/tools/bertviz/) | 8,193 | 1 | Apache-2.0 | Visualize attention in Transformer language models such as BERT and GPT-2. | | 8 | [TensorBoard](https://awesomedataviz.com/tools/tensorboard/) | 7,229 | 40 | Apache-2.0 | TensorFlow's visualization toolkit for metrics, model graphs, embeddings and more. | | 9 | [Aim](https://awesomedataviz.com/tools/aim/) | 6,276 | 1 | Apache-2.0 | Experiment tracker with a UI to explore and compare ML runs and metrics. | | 10 | [Embedding Atlas](https://awesomedataviz.com/tools/embedding-atlas/) | 4,965 | 134 | MIT | Interactive visualization of large embeddings with search, filtering and density views, by Apple. | | 11 | [Yellowbrick](https://awesomedataviz.com/tools/yellowbrick/) | 4,407 | 0 | Apache-2.0 | Visual analysis and diagnostic tools for machine learning model selection with scikit-learn. | | 12 | [LIT](https://awesomedataviz.com/tools/lit/) | 3,668 | 0 | Apache-2.0 | Learning Interpretability Tool: interactive visual analysis of ML model behavior, by Google PAIR. | | 13 | [TensorWatch](https://awesomedataviz.com/tools/tensorwatch/) | 3,474 | 6 | MIT | Debugging and visualization tool for data science and machine learning | | 14 | [dtreeviz](https://awesomedataviz.com/tools/dtreeviz/) | 3,159 | 18 | MIT | Decision tree visualization and model interpretation library for Python. | | 15 | [Comet](https://awesomedataviz.com/tools/comet/) | 175 | 38 | MIT | An MLOps platform for tracking, visualizing, and debugging your machine learning workflows from training straight through to production. | Source: https://awesomedataviz.com/categories/machine-learning/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## C# & .NET charting libraries > Charts for WinForms, WPF, MAUI, Avalonia and Blazor. 6 tools, ranked by GitHub stars. Charting libraries for C# and .NET, covering desktop and mobile UI frameworks such as WinForms, WPF, MAUI and Avalonia, web UIs with Blazor, and server-side image generation. Most install as NuGet packages. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [ScottPlot](https://awesomedataviz.com/tools/scottplot/) | 6,766 | 126 | MIT | Interactive plotting library for .NET with WinForms, WPF, Avalonia, Blazor and other controls. | | 2 | [LiveCharts2](https://awesomedataviz.com/tools/livecharts2/) | 5,482 | 1,374 | MIT | Animated, interactive charts, maps and gauges for .NET UI frameworks. | | 3 | [OxyPlot](https://awesomedataviz.com/tools/oxyplot/) | 3,541 | 1 | MIT | Cross-platform plotting library for .NET. | | 4 | [Microcharts](https://awesomedataviz.com/tools/microcharts/) | 2,075 | 47 | MIT | Simple cross-platform charts for .NET, drawn with SkiaSharp. | | 5 | [Mapsui](https://awesomedataviz.com/tools/mapsui/) | 1,573 | 650 | MIT | .NET map component for MAUI, Avalonia, Uno Platform, Blazor, WPF and WinUI. | | 6 | [MSAGL](https://awesomedataviz.com/tools/msagl/) | 1,499 | 7 | Other | Microsoft Automatic Graph Layout: tools for graph layout and viewing in .NET. | Source: https://awesomedataviz.com/categories/dotnet/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Python data visualization libraries > From Matplotlib and Seaborn to interactive and 3D plotting. 48 tools, ranked by GitHub stars. Python has one of the richest data visualization ecosystems of any language. Matplotlib is the foundation for static plots and Seaborn builds statistical graphics on top of it. Plotly (Python), Bokeh and HoloViews produce interactive charts for notebooks and the web, and Vega-Altair offers a declarative grammar based on Vega-Lite. For 3D and GPU-accelerated scientific visualization, look at VisPy, PyVista and Mayavi. For quick looks at a whole dataset, profiling tools such as ydata-profiling generate exploratory reports in one call. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [Streamlit](https://awesomedataviz.com/tools/streamlit/) | 45,895 | 2,413 | Apache-2.0 | Framework for turning Python scripts into interactive data apps. | | 2 | [Dash](https://awesomedataviz.com/tools/dash/) | 24,441 | 1,348 | MIT | Framework for building data apps and dashboards in Python, built on Plotly.js and React. | | 3 | [Matplotlib](https://awesomedataviz.com/tools/matplotlib/) | 23,323 | 2,023 | PSF-2.0 | 2D plotting library. | | 4 | [Bokeh](https://awesomedataviz.com/tools/bokeh/) | 20,455 | 344 | BSD-3-Clause | Interactive Web Plotting for Python. | | 5 | [Taipy](https://awesomedataviz.com/tools/taipy/) | 19,443 | 69 | Apache-2.0 | Python framework for building data and AI web applications with interactive charts and dashboards. | | 6 | [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/) | 18,822 | 739 | MIT | Interactive web based visualization built on top of plotly.js | | 7 | [PyGWalker](https://awesomedataviz.com/tools/pygwalker/) | 15,983 | 154 | Apache-2.0 | Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker. | | 8 | [pyecharts](https://awesomedataviz.com/tools/pyecharts/) | 15,774 | 2 | MIT | Python binding for Echarts library. | | 9 | [Seaborn](https://awesomedataviz.com/tools/seaborn/) | 14,056 | 18 | BSD-3-Clause | A library for making attractive and informative statistical graphics. | | 10 | [ydata-profiling](https://awesomedataviz.com/tools/ydata-profiling/) | 13,719 | 8 | MIT | Generates statistical analytic reports with visualization for quick data analysis (formerly pandas-profiling). | | 11 | [Rerun](https://awesomedataviz.com/tools/rerun/) | 11,543 | 3,095 | Apache-2.0 | An SDK for logging computer vision and robotics data paired with a visualizer for exploring that data over time. | | 12 | [WordCloud](https://awesomedataviz.com/tools/wordcloud/) | 10,536 | 5 | MIT | Word cloud generator for Python. | | 13 | [Vega-Altair](https://awesomedataviz.com/tools/altair/) | 10,491 | 153 | BSD-3-Clause | Declarative statistical visualizations, based on Vega-Lite. | | 14 | [SciencePlots](https://awesomedataviz.com/tools/scienceplots/) | 9,270 | 10 | MIT | Matplotlib styles for scientific figures and journal publications. | | 15 | [folium](https://awesomedataviz.com/tools/folium/) | 7,409 | 161 | MIT | Builds interactive Leaflet.js maps from Python data. | | 16 | [Voilà](https://awesomedataviz.com/tools/voila/) | 5,947 | 12 | BSD | Turns Jupyter notebooks into standalone interactive web applications. | | 17 | [Panel](https://awesomedataviz.com/tools/panel/) | 5,782 | 392 | BSD-3-Clause | Data exploration and web app framework for Python that works with many plotting libraries. | | 18 | [plotnine](https://awesomedataviz.com/tools/plotnine/) | 4,770 | 490 | MIT | Grammar of graphics for Python, based on R's ggplot2. | | 19 | [mplfinance](https://awesomedataviz.com/tools/mplfinance/) | 4,439 | 0 | BSD-style | Financial market data visualization (candlestick, OHLC, volume) using matplotlib. | | 20 | [PyQtGraph](https://awesomedataviz.com/tools/pyqtgraph/) | 4,421 | 355 | MIT | Interactive and realtime 2D/3D/Image plotting and science/engineering widgets. | | 21 | [missingno](https://awesomedataviz.com/tools/missingno/) | 4,211 | 0 | MIT | Provides flexible toolset of data-visualization utilities that allows quick visual summary of the completeness of your dataset, based on matplotlib. | | 22 | [PyVista](https://awesomedataviz.com/tools/pyvista/) | 3,832 | 884 | MIT | 3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK) | | 23 | [leafmap](https://awesomedataviz.com/tools/leafmap/) | 3,782 | 147 | MIT | Interactive mapping and geospatial analysis in Jupyter with multiple mapping backends. | | 24 | [bqplot](https://awesomedataviz.com/tools/bqplot/) | 3,693 | 21 | Apache-2.0 | Plotting library for IPython/Jupyter notebooks. | | 25 | [ggpy](https://awesomedataviz.com/tools/ggpy/) | 3,688 | 0 | BSD-2-Clause | Plotting system based on R's ggplot2. | | 26 | [Chartify](https://awesomedataviz.com/tools/chartify/) | 3,653 | 0 | Apache-2.0 | Bokeh wrapper that makes it easy for data scientists to create charts. | | 27 | [VisPy](https://awesomedataviz.com/tools/vispy/) | 3,603 | 62 | BSD-3-Clause | High-performance scientific visualization based on OpenGL. | | 28 | [Datashader](https://awesomedataviz.com/tools/datashader/) | 3,562 | 48 | BSD-3-Clause | Renders very large datasets into accurate images by rasterizing them. | | 29 | [VTK](https://awesomedataviz.com/tools/vtk/) | 3,211 | 5,558 | BSD | Open-source library for 3d Graphics, image processing and visualization. | | 30 | [HoloViews](https://awesomedataviz.com/tools/holoviews/) | 2,910 | 321 | BSD-3-Clause | Complex and declarative visualizations from annotated data. | | 31 | [napari](https://awesomedataviz.com/tools/napari/) | 2,771 | 641 | BSD-3-Clause | Fast, interactive viewer for multi-dimensional images in Python. | | 32 | [vedo](https://awesomedataviz.com/tools/vedo/) | 2,272 | 263 | MIT | Library for scientific analysis and visualization of 3D objects based on VTK. | | 33 | [Plotext](https://awesomedataviz.com/tools/plotext/) | 2,204 | 27 | MIT | Plots data directly in the terminal with a matplotlib-like syntax. | | 34 | [Lets-Plot](https://awesomedataviz.com/tools/lets-plot/) | 1,783 | 606 | MIT | Grammar of graphics plotting library for Python and Kotlin, by JetBrains. | | 35 | [Shiny for Python](https://awesomedataviz.com/tools/shiny-for-python/) | 1,756 | 217 | MIT | Python version of the Shiny reactive framework for interactive data apps. | | 36 | [Cartopy](https://awesomedataviz.com/tools/cartopy/) | 1,621 | 212 | BSD-3-Clause | Cartographic projections and geospatial data plotting with matplotlib. | | 37 | [Mayavi](https://awesomedataviz.com/tools/mayavi/) | 1,412 | 43 | BSD-3-Clause | Interactive scientific data visualization and 3D plotting in Python. | | 38 | [glumpy](https://awesomedataviz.com/tools/glumpy/) | 1,280 | 0 | BSD-3-Clause | OpenGL scientific visualizations library. | | 39 | [Veusz](https://awesomedataviz.com/tools/veusz/) | 1,051 | 41 | GPL-2.0 | Python multiplatform GUI plotting tool and graphing library | | 40 | [pptk](https://awesomedataviz.com/tools/pptk/) | 635 | 0 | MIT | Visualize and work with 2D/3D pointclouds | | 41 | [yt](https://awesomedataviz.com/tools/yt/) | 559 | 400 | BSD-3-Clause | Toolkit for analysis and visualization of volumetric data. | | 42 | [uniplot](https://awesomedataviz.com/tools/uniplot/) | 460 | 31 | MIT | Lightweight plotting to the terminal. 4x resolution via Unicode. | | 43 | [Toyplot](https://awesomedataviz.com/tools/toyplot/) | 449 | 26 | BSD | The kid-sized plotting toolkit for Python with grownup-sized goals. | | 44 | [diagram](https://awesomedataviz.com/tools/diagram/) | 408 | 0 | MIT | Text mode diagrams using UTF-8 characters | | 45 | [Quibbler](https://awesomedataviz.com/tools/quibbler/) | 332 | 0 | MIT | Your data and anything you plot is effortlessly live and interactive. | | 46 | [ipychart](https://awesomedataviz.com/tools/ipychart/) | 133 | 0 | MIT | The power of Chart.js in Jupyter Notebook. | | 47 | [three.py](https://awesomedataviz.com/tools/three-py/) | 121 | 0 | MIT | Easy to use 3D library based on PyOpenGL. Inspired by Three.js. | | 48 | [syd](https://awesomedataviz.com/tools/syd/) | 30 | 12 | GPL-3.0 | A package for making GUIs around matplotlib figures easy, fast, and streamlined. | Source: https://awesomedataviz.com/categories/python/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## R data visualization packages > ggplot2, interactive graphics and Shiny apps. 19 tools, ranked by GitHub stars. R's visualization ecosystem centers on ggplot2, an implementation of the grammar of graphics that most R users learn first. Interactive alternatives include plotly (R) and visNetwork, rgl covers 3D graphics, and Shiny turns analyses into interactive web applications. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [ggplot2](https://awesomedataviz.com/tools/ggplot2/) | 7,005 | 86 | MIT | A plotting system based on the grammar of graphics. | | 2 | [Shiny](https://awesomedataviz.com/tools/shiny/) | 5,694 | 63 | MIT | Framework for creating interactive applications/visualisations | | 3 | [plotly (R)](https://awesomedataviz.com/tools/plotly-r/) | 2,682 | 19 | MIT | Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams | | 4 | [patchwork](https://awesomedataviz.com/tools/patchwork/) | 2,615 | 0 | MIT | Composes multiple ggplot2 plots into a single figure. | | 5 | [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/) | 2,207 | 84 | MIT | Ggplot2-based plots with statistical test details included in the graphic. | | 6 | [rayshader](https://awesomedataviz.com/tools/rayshader/) | 2,182 | 33 | GPL-3.0 | 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. | | 7 | [gt](https://awesomedataviz.com/tools/gt/) | 2,161 | 939 | MIT | Builds publication-quality display tables in R. | | 8 | [gganimate](https://awesomedataviz.com/tools/gganimate/) | 1,983 | 0 | MIT | Grammar of animated graphics that extends ggplot2. | | 9 | [esquisse](https://awesomedataviz.com/tools/esquisse/) | 1,865 | 0 | GPL-3.0 | Drag-and-drop interface for building ggplot2 charts in RStudio or Shiny. | | 10 | [DiagrammeR](https://awesomedataviz.com/tools/diagrammer/) | 1,745 | 22 | MIT | Graph and network diagrams in R, rendered with Graphviz and mermaid. | | 11 | [ComplexHeatmap](https://awesomedataviz.com/tools/complexheatmap/) | 1,557 | 3 | Other | Highly customizable heatmaps for genomic and other matrix data (Bioconductor). | | 12 | [ggrepel](https://awesomedataviz.com/tools/ggrepel/) | 1,261 | 30 | GPL-3.0 | Repels overlapping text labels away from each other in ggplot2 plots. | | 13 | [ggraph](https://awesomedataviz.com/tools/ggraph/) | 1,118 | 0 | MIT | Grammar of graphics for graphs and networks, extending ggplot2. | | 14 | [Leaflet for R](https://awesomedataviz.com/tools/leaflet-for-r/) | 841 | 0 | MIT | R interface to the Leaflet JavaScript library for interactive maps. | | 15 | [ggvis](https://awesomedataviz.com/tools/ggvis/) | 707 | 3 | GPL-2.0 | A data visualization package with a syntax similar to ggplot2 which allows you to create rich interactive graphics. | | 16 | [visNetwork](https://awesomedataviz.com/tools/visnetwork/) | 563 | 0 | MIT | Interactive network visualisations | | 17 | [rbokeh](https://awesomedataviz.com/tools/rbokeh/) | 311 | 0 | MIT | R Interface to Bokeh. | | 18 | [rgl](https://awesomedataviz.com/tools/rgl/) | 103 | 36 | GPL-2.0 | 3D Visualization Using OpenGL | | 19 | [lattice](https://awesomedataviz.com/tools/lattice/) | 74 | 16 | GPL-2.0-or-later | Trellis graphics for R | Source: https://awesomedataviz.com/categories/r/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Ruby charting libraries > Charts for Ruby and Rails applications. 4 tools, ranked by GitHub stars. Ruby libraries for adding charts to applications, typically Rails apps that render a JavaScript chart library from server-side data. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [Chartkick](https://awesomedataviz.com/tools/chartkick/) | 6,528 | 10 | MIT | Create charts with one line of Ruby. | | 2 | [YouPlot](https://awesomedataviz.com/tools/youplot/) | 4,857 | 40 | MIT | Command-line tool that draws plots in the terminal from piped data. | | 3 | [Blazer](https://awesomedataviz.com/tools/blazer/) | 4,802 | 254 | MIT | Business intelligence tool for Rails apps: explore data with SQL and build charts and dashboards. | | 4 | [Gruff](https://awesomedataviz.com/tools/gruff/) | 1,398 | 37 | MIT | Graphing library for Ruby that renders charts as images using RMagick. | Source: https://awesomedataviz.com/categories/ruby/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Rust plotting & visualization libraries > Plotting crates, terminal charts and data viewers. 4 tools, ranked by GitHub stars. Rust crates for plotting and visualization, from charts in the terminal to SDKs and viewers for multimodal and robotics data. They are added with cargo add, and many compile to WebAssembly for use in the browser. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [Plotters](https://awesomedataviz.com/tools/plotters/) | 4,632 | 23 | MIT | Drawing library for data plotting in Rust, with bitmap, SVG, WebAssembly and GUI backends. | | 2 | [Charming](https://awesomedataviz.com/tools/charming/) | 2,600 | 12 | Apache-2.0 | Chart rendering library for Rust powered by Apache ECharts. | | 3 | [Plotly.rs](https://awesomedataviz.com/tools/plotly-rs/) | 1,457 | 53 | MIT | Plotly.js-based interactive plotting library for Rust. | | 4 | [malevich](https://awesomedataviz.com/tools/malevich/) | 70 | 288 | Apache-2.0 | Terminal plotting: line, scatter, bar, histogram, heatmap, box plot, violin and more, with automatic axes. | Source: https://awesomedataviz.com/categories/rust/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Diagrams as code > Diagrams and charts generated from plain-text descriptions. 11 tools, ranked by GitHub stars. Tools that turn plain-text descriptions into diagrams, so diagrams live in version control next to the code and documentation they describe. Mermaid renders flowcharts, sequence diagrams and more from Markdown-like text and is supported in GitHub Markdown; WaveDrom draws digital timing diagrams. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [Mermaid](https://awesomedataviz.com/tools/mermaid/) | 90,531 | 2,472 | MIT | Generate diagrams and flowcharts from markdown-like text definitions, with a live editor. | | 2 | [Diagrams](https://awesomedataviz.com/tools/diagrams/) | 42,673 | 48 | MIT | Diagram as code in Python for prototyping cloud system architectures. | | 3 | [D2](https://awesomedataviz.com/tools/d2/) | 25,564 | 324 | MPL-2.0 | Declarative diagram scripting language that turns text into diagrams. | | 4 | [PlantUML](https://awesomedataviz.com/tools/plantuml/) | 13,352 | 846 | LGPL-3.0 | Generates UML, Gantt, mind map and other diagrams from plain text. | | 5 | [Markmap](https://awesomedataviz.com/tools/markmap/) | 13,147 | 4 | MIT | Builds interactive mind maps from Markdown. | | 6 | [flowchart.js](https://awesomedataviz.com/tools/flowchart-js/) | 8,700 | 1 | MIT | Draws SVG flowcharts from a textual description. | | 7 | [Penrose](https://awesomedataviz.com/tools/penrose/) | 7,985 | 48 | MIT | Creates diagrams from mathematical notation in plain text, from Carnegie Mellon University. | | 8 | [LikeC4](https://awesomedataviz.com/tools/likec4/) | 5,809 | 1,831 | MIT | Architecture-as-code language and tools that generate live, interactive diagrams. | | 9 | [Kroki](https://awesomedataviz.com/tools/kroki/) | 4,358 | 204 | MIT | Unified API that renders diagrams from many text formats, including PlantUML, Mermaid, Graphviz and D2. | | 10 | [WaveDrom](https://awesomedataviz.com/tools/wavedrom/) | 3,501 | 12 | MIT | Draws timing diagrams and waveforms from simple textual descriptions. | | 11 | [PGFPlots](https://awesomedataviz.com/tools/pgfplots/) | 257 | 13 | – | TeX package for drawing 2D and 3D plots directly in LaTeX documents. | Source: https://awesomedataviz.com/categories/diagrams-as-code/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Data visualization apps & tools > Standalone apps and language-agnostic tools. 28 tools, ranked by GitHub stars. Standalone applications and language-agnostic tools: desktop apps for exploring large graphs such as Gephi, web apps that turn spreadsheets into charts such as RAWGraphs, geospatial explorers such as Kepler.gl, and command-line tools such as Graphviz. | # | Tool | GitHub stars | Commits (12 mo) | License | Description | |---:|---|---:|---:|---|---| | 1 | [ChartDB](https://awesomedataviz.com/tools/chartdb/) | 22,987 | 116 | AGPL-3.0 | An Open-source tool to visualize database schemas and generate ER diagrams from a single query. | | 2 | [FlameGraph](https://awesomedataviz.com/tools/flamegraph/) | 19,785 | 0 | – | Stack trace visualizer that generates interactive SVG flame graphs from profiling data. | | 3 | [Data Formulator](https://awesomedataviz.com/tools/data-formulator/) | 17,525 | 930 | MIT | AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. | | 4 | [Sampler](https://awesomedataviz.com/tools/sampler/) | 14,810 | 0 | GPL-3.0 | Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. | | 5 | [QGIS](https://awesomedataviz.com/tools/qgis/) | 14,461 | 6,488 | GPL-2.0 | Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. | | 6 | [Gource](https://awesomedataviz.com/tools/gource/) | 13,159 | 3 | GPL-3.0 | Animated visualization of software version control history. | | 7 | [Kepler.gl](https://awesomedataviz.com/tools/kepler-gl/) | 12,033 | 402 | MIT | Geospatial analysis tool for large-scale data sets. | | 8 | [VisiData](https://awesomedataviz.com/tools/visidata/) | 9,317 | 576 | GPL-3.0 | Terminal spreadsheet multitool for exploring and arranging tabular data, with basic plotting. | | 9 | [RAWGraphs](https://awesomedataviz.com/tools/rawgraphs/) | 9,033 | 0 | Apache-2.0 | Create web visualizations from CSV or Excel files. | | 10 | [draw.io](https://awesomedataviz.com/tools/draw-io/) | 8,555 | 65 | Apache-2.0 | Client-side JavaScript editor for flowcharts, network, UML and other diagrams. | | 11 | [SandDance](https://awesomedataviz.com/tools/sanddance/) | 7,147 | 67 | MIT | Visual data exploration and presentation with animated unit visualizations, from Microsoft Research. | | 12 | [Gephi](https://awesomedataviz.com/tools/gephi/) | 6,658 | 1,506 | GPL-3.0 | An open-source platform for visualizing and manipulating large graphs | | 13 | [Spark](https://awesomedataviz.com/tools/spark/) | 6,068 | 0 | MIT | Sparklines for the shell. It has several implementations in different languages. | | 14 | [Orange](https://awesomedataviz.com/tools/orange/) | 5,717 | 309 | Other | Visual programming tool for data mining, machine learning and interactive data visualization. | | 15 | [RATH](https://awesomedataviz.com/tools/rath/) | 4,686 | 29 | AGPL-3.0 | Automatic Exploratory Data Analysis & Data Visualization tool which is powered by an AI-assisted Augmented Analytics engine. | | 16 | [Charted](https://awesomedataviz.com/tools/charted/) | 2,745 | 0 | MIT | A charting tool that produces automatic, shareable charts from any data file. | | 17 | [Graphviz](https://awesomedataviz.com/tools/graphviz/) | 1,473 | – | EPL-2.0 | Open source graph visualization command line tool and library. From input text to SVG,PDF,interactive web graph browser. | | 18 | [DAC](https://awesomedataviz.com/tools/dac/) | 779 | 279 | AGPL-3.0 | Dashboard-as-code tool that builds interactive dashboards from YAML and TSX definitions | | 19 | [Cytoscape](https://awesomedataviz.com/tools/cytoscape/) | 731 | 4 | – | Desktop platform for network analysis and visualization, widely used in bioinformatics. | | 20 | [LabPlot](https://awesomedataviz.com/tools/labplot/) | 486 | 1,428 | – | KDE application for interactive scientific plotting, data analysis and visualization. | | 21 | [sankeydiagram.net](https://awesomedataviz.com/tools/sankeydiagram-net/) | 123 | 2 | MIT + Commons Clause | Web app for creating and sharing Sankey diagrams of flows and budgets without code. | | 22 | [Squey](https://awesomedataviz.com/tools/squey/) | 23 | – | MIT | Visualization software for exploring and understanding large amounts of tabular data (using parallel coordinates, timeseries and scatter plots). | | 23 | [Resseract Lite](https://awesomedataviz.com/tools/resseract-lite/) | 7 | 0 | Apache-2.0 | A Data Analytics and Visualization Tool with flexible architecture to visualize and analyse data | | 24 | [ink-uplot](https://awesomedataviz.com/tools/ink-uplot/) | 1 | 81 | MIT | Render uPlot charts in the terminal (React Ink) with truecolor Unicode and kitty/sixel/iTerm2 graphics. | | 25 | [csvtodashboard](https://awesomedataviz.com/tools/csvtodashboard/) | – | – | – | Turn a CSV or Excel file into an auto-built dashboard in the browser - client-side, no upload. | | 26 | [ERD Lab](https://awesomedataviz.com/tools/erd-lab/) | – | – | – | Free cloud based entity relationship diagram (ERD) tool made for developers. | | 27 | [gnuplot](https://awesomedataviz.com/tools/gnuplot/) | – | – | – | Command-line driven program for 2D and 3D plots, with many output formats. | | 28 | [Plotivy](https://awesomedataviz.com/tools/plotivy/) | – | – | – | Scientific data visualization tool, with AI-generated reproducible Python code, and research-oriented design best practices built in. | Source: https://awesomedataviz.com/categories/apps/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). # Tools ## D3.js > JavaScript library for producing dynamic, data-driven visualizations with SVG, Canvas and HTML. - Category: [D3.js](https://awesomedataviz.com/categories/d3/) - Website: https://d3js.org - Repository: https://github.com/d3/d3 - License: ISC - Language: JavaScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 113,802 - Commits in the last 12 months: 2 - Contributors: 136 - Last commit: May 28, 2026 - Latest release: v7.9.0 (Mar 12, 2024) - Install (npm): `npm install d3`, 25.7M downloads per week ### Overview D3.js is an open-source JavaScript visualization library released under the ISC license. Its GitHub repository has 113,802 stars, 22,637 forks, and 136 contributors. It is maintained with 2 commits in the last 12 months; the most recent commit was on May 28, 2026. The latest release, v7.9.0, was published on Mar 12, 2024. On npm it is downloaded about 25.7M times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) ### Comparisons - [Chart.js vs D3.js](https://awesomedataviz.com/compare/chart-js-vs-d3/) - [D3.js vs Apache ECharts](https://awesomedataviz.com/compare/d3-vs-echarts/) - [D3.js vs Plotly.js](https://awesomedataviz.com/compare/d3-vs-plotly-js/) - [D3.js vs Observable Plot](https://awesomedataviz.com/compare/d3-vs-observable-plot/) - [D3.js vs visx](https://awesomedataviz.com/compare/d3-vs-visx/) Source: https://awesomedataviz.com/tools/d3/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Mermaid > Generate diagrams and flowcharts from markdown-like text definitions, with a live editor. - Category: [Diagrams as code](https://awesomedataviz.com/categories/diagrams-as-code/) - Website: https://mermaid.ai/open-source/ - Repository: https://github.com/mermaid-js/mermaid - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 90,531 - Commits in the last 12 months: 2,472 - Contributors: 365 - Last commit: Oct 2, 2026 - Latest release: @mermaid-js/tiny@12.1.0 (Oct 2, 2026) - Install (npm): `npm install mermaid`, 20M downloads per week - Topics: Diagrams & diagrams as code ### Overview Mermaid is an open-source diagram-as-code tool released under the MIT license. Its GitHub repository has 90,531 stars, 9,322 forks, and 365 contributors. It is actively developed with 2,472 commits in the last 12 months. The latest release, @mermaid-js/tiny@12.1.0, was published on Oct 2, 2026. On npm it is downloaded about 20M times per week. ### Alternatives - [Diagrams](https://awesomedataviz.com/tools/diagrams/): Diagram as code in Python for prototyping cloud system architectures. (42.7K stars) - [D2](https://awesomedataviz.com/tools/d2/): Declarative diagram scripting language that turns text into diagrams. (25.6K stars) - [PlantUML](https://awesomedataviz.com/tools/plantuml/): Generates UML, Gantt, mind map and other diagrams from plain text. (13.4K stars) - [Markmap](https://awesomedataviz.com/tools/markmap/): Builds interactive mind maps from Markdown. (13.1K stars) - [flowchart.js](https://awesomedataviz.com/tools/flowchart-js/): Draws SVG flowcharts from a textual description. (8.7K stars) - [Penrose](https://awesomedataviz.com/tools/penrose/): Creates diagrams from mathematical notation in plain text, from Carnegie Mellon University. (8K stars) ### Comparisons - [Diagrams vs Mermaid](https://awesomedataviz.com/compare/diagrams-vs-mermaid/) - [D2 vs Mermaid](https://awesomedataviz.com/compare/d2-vs-mermaid/) - [Mermaid vs PlantUML](https://awesomedataviz.com/compare/mermaid-vs-plantuml/) - [Markmap vs Mermaid](https://awesomedataviz.com/compare/markmap-vs-mermaid/) - [Graphviz vs Mermaid](https://awesomedataviz.com/compare/graphviz-vs-mermaid/) Source: https://awesomedataviz.com/tools/mermaid/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Grafana > Observability and data visualization platform for metrics, logs and traces from many data sources. - Category: [Open-source dashboards & BI tools](https://awesomedataviz.com/categories/dashboards-and-bi/) - Website: https://grafana.com - Repository: https://github.com/grafana/grafana - License: AGPL-3.0 - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 77,071 - Commits in the last 12 months: 11,330 - Contributors: 373 - Last commit: Oct 4, 2026 - Latest release: v13.2.3 (Sep 29, 2026) - Install (Go): `go get github.com/grafana/grafana` - Topics: Dashboards & BI ### Overview Grafana is an open-source dashboard and BI tool released under the AGPL-3.0 license. Its GitHub repository has 77,071 stars, 14,817 forks, and 373 contributors. It is actively developed with 11,330 commits in the last 12 months. The latest release, v13.2.3, was published on Sep 29, 2026. ### Alternatives - [Apache Superset](https://awesomedataviz.com/tools/superset/): Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. (75K stars) - [Metabase](https://awesomedataviz.com/tools/metabase/): Business intelligence tool for querying data and building dashboards, with embedded analytics. (49.5K stars) - [Redash](https://awesomedataviz.com/tools/redash/): Query data sources with SQL, then visualize the results and build dashboards. (28.8K stars) - [Kibana](https://awesomedataviz.com/tools/kibana/): Visualization and dashboard UI for data stored in Elasticsearch. (21.3K stars) - [Evidence](https://awesomedataviz.com/tools/evidence/): Business intelligence as code: build reports and dashboards with SQL and Markdown. (7K stars) - [Lightdash](https://awesomedataviz.com/tools/lightdash/): BI tool that turns dbt projects into metrics, charts and dashboards. (6.2K stars) ### Comparisons - [Grafana vs Apache Superset](https://awesomedataviz.com/compare/grafana-vs-superset/) - [Grafana vs Metabase](https://awesomedataviz.com/compare/grafana-vs-metabase/) - [Grafana vs Redash](https://awesomedataviz.com/compare/grafana-vs-redash/) - [Grafana vs Kibana](https://awesomedataviz.com/compare/grafana-vs-kibana/) Source: https://awesomedataviz.com/tools/grafana/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Apache Superset > Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. - Category: [Open-source dashboards & BI tools](https://awesomedataviz.com/categories/dashboards-and-bi/) - Website: https://superset.apache.org/ - Repository: https://github.com/apache/superset - License: Apache-2.0 - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 75,035 - Commits in the last 12 months: 5,646 - Contributors: 420 - Last commit: Oct 4, 2026 - Latest release: 6.1.0 (May 13, 2026) - Install (PyPI): `pip install apache-superset`, 86.7K downloads per week - Topics: Dashboards & BI, Exploratory data analysis tools ### Overview Apache Superset is an open-source dashboard and BI tool released under the Apache-2.0 license. Its GitHub repository has 75,035 stars, 18,428 forks, and 420 contributors. It is actively developed with 5,646 commits in the last 12 months. The latest release, 6.1.0, was published on May 13, 2026. On PyPI it is downloaded about 86.7K times per week. ### Alternatives - [Grafana](https://awesomedataviz.com/tools/grafana/): Observability and data visualization platform for metrics, logs and traces from many data sources. (77.1K stars) - [Metabase](https://awesomedataviz.com/tools/metabase/): Business intelligence tool for querying data and building dashboards, with embedded analytics. (49.5K stars) - [Redash](https://awesomedataviz.com/tools/redash/): Query data sources with SQL, then visualize the results and build dashboards. (28.8K stars) - [Kibana](https://awesomedataviz.com/tools/kibana/): Visualization and dashboard UI for data stored in Elasticsearch. (21.3K stars) - [Evidence](https://awesomedataviz.com/tools/evidence/): Business intelligence as code: build reports and dashboards with SQL and Markdown. (7K stars) - [Lightdash](https://awesomedataviz.com/tools/lightdash/): BI tool that turns dbt projects into metrics, charts and dashboards. (6.2K stars) ### Comparisons - [Grafana vs Apache Superset](https://awesomedataviz.com/compare/grafana-vs-superset/) - [Metabase vs Apache Superset](https://awesomedataviz.com/compare/metabase-vs-superset/) - [Redash vs Apache Superset](https://awesomedataviz.com/compare/redash-vs-superset/) - [Kibana vs Apache Superset](https://awesomedataviz.com/compare/kibana-vs-superset/) Source: https://awesomedataviz.com/tools/superset/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Chart.js > Charts with the canvas tag. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://www.chartjs.org/ - Repository: https://github.com/chartjs/Chart.js - License: MIT - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 67,733 - Commits in the last 12 months: 21 - Contributors: 426 - Last commit: Oct 3, 2026 - Latest release: v4.5.1 (Oct 13, 2025) - Install (npm): `npm install chart.js`, 15.7M downloads per week ### Overview Chart.js is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 67,733 stars, 11,947 forks, and 426 contributors. It is actively developed with 21 commits in the last 12 months. The latest release, v4.5.1, was published on Oct 13, 2025. On npm it is downloaded about 15.7M times per week. ### Alternatives - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) - [Chartist.js](https://awesomedataviz.com/tools/chartist-js/): Responsive charts with great browser compatibility. (13.4K stars) ### Comparisons - [Chart.js vs Apache ECharts](https://awesomedataviz.com/compare/chart-js-vs-echarts/) - [Chart.js vs Plotly.js](https://awesomedataviz.com/compare/chart-js-vs-plotly-js/) - [Chart.js vs Lightweight Charts](https://awesomedataviz.com/compare/chart-js-vs-lightweight-charts/) - [ApexCharts vs Chart.js](https://awesomedataviz.com/compare/apexcharts-vs-chart-js/) - [Chart.js vs D3.js](https://awesomedataviz.com/compare/chart-js-vs-d3/) - [Chart.js vs Recharts](https://awesomedataviz.com/compare/chart-js-vs-recharts/) - [Chart.js vs uPlot](https://awesomedataviz.com/compare/chart-js-vs-uplot/) Source: https://awesomedataviz.com/tools/chart-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Apache ECharts > Highly customizable and interactive charts ready for big datasets. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://echarts.apache.org - Repository: https://github.com/apache/echarts - License: Apache-2.0 - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 67,449 - Commits in the last 12 months: 266 - Contributors: 274 - Last commit: Oct 4, 2026 - Latest release: 6.1.0 (May 19, 2026) - Install (npm): `npm install echarts`, 6.7M downloads per week - Topics: Visualizing large datasets ### Overview Apache ECharts is an open-source JavaScript charting library released under the Apache-2.0 license. Its GitHub repository has 67,449 stars, 19,817 forks, and 274 contributors. It is actively developed with 266 commits in the last 12 months. The latest release, 6.1.0, was published on May 19, 2026. On npm it is downloaded about 6.7M times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) - [Chartist.js](https://awesomedataviz.com/tools/chartist-js/): Responsive charts with great browser compatibility. (13.4K stars) ### Comparisons - [Chart.js vs Apache ECharts](https://awesomedataviz.com/compare/chart-js-vs-echarts/) - [Apache ECharts vs Plotly.js](https://awesomedataviz.com/compare/echarts-vs-plotly-js/) - [Apache ECharts vs Lightweight Charts](https://awesomedataviz.com/compare/echarts-vs-lightweight-charts/) - [ApexCharts vs Apache ECharts](https://awesomedataviz.com/compare/apexcharts-vs-echarts/) - [D3.js vs Apache ECharts](https://awesomedataviz.com/compare/d3-vs-echarts/) Source: https://awesomedataviz.com/tools/echarts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Metabase > Business intelligence tool for querying data and building dashboards, with embedded analytics. - Category: [Open-source dashboards & BI tools](https://awesomedataviz.com/categories/dashboards-and-bi/) - Website: https://metabase.com - Repository: https://github.com/metabase/metabase - License: Other - Language: Clojure - Status: Active (commits in the last 90 days) - GitHub stars: 49,536 - Commits in the last 12 months: 6,704 - Contributors: 390 - Last commit: Oct 4, 2026 - Latest release: v0.63.19 (Oct 1, 2026) - Topics: Dashboards & BI ### Overview Metabase is a dashboard and BI tool. Its GitHub repository has 49,536 stars, 6,876 forks, and 390 contributors. It is actively developed with 6,704 commits in the last 12 months. The latest release, v0.63.19, was published on Oct 1, 2026. ### Alternatives - [Grafana](https://awesomedataviz.com/tools/grafana/): Observability and data visualization platform for metrics, logs and traces from many data sources. (77.1K stars) - [Apache Superset](https://awesomedataviz.com/tools/superset/): Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. (75K stars) - [Redash](https://awesomedataviz.com/tools/redash/): Query data sources with SQL, then visualize the results and build dashboards. (28.8K stars) - [Kibana](https://awesomedataviz.com/tools/kibana/): Visualization and dashboard UI for data stored in Elasticsearch. (21.3K stars) - [Evidence](https://awesomedataviz.com/tools/evidence/): Business intelligence as code: build reports and dashboards with SQL and Markdown. (7K stars) - [Lightdash](https://awesomedataviz.com/tools/lightdash/): BI tool that turns dbt projects into metrics, charts and dashboards. (6.2K stars) ### Comparisons - [Grafana vs Metabase](https://awesomedataviz.com/compare/grafana-vs-metabase/) - [Metabase vs Apache Superset](https://awesomedataviz.com/compare/metabase-vs-superset/) - [Metabase vs Redash](https://awesomedataviz.com/compare/metabase-vs-redash/) - [Kibana vs Metabase](https://awesomedataviz.com/compare/kibana-vs-metabase/) Source: https://awesomedataviz.com/tools/metabase/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Streamlit > Framework for turning Python scripts into interactive data apps. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://streamlit.io - Repository: https://github.com/streamlit/streamlit - License: Apache-2.0 - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 45,895 - Commits in the last 12 months: 2,413 - Contributors: 319 - Last commit: Oct 4, 2026 - Latest release: 1.65.0 (Oct 2, 2026) - Install (PyPI): `pip install streamlit`, 4.7M downloads per week ### Overview Streamlit is an open-source Python visualization library released under the Apache-2.0 license. Its GitHub repository has 45,895 stars, 4,404 forks, and 319 contributors. It is actively developed with 2,413 commits in the last 12 months. The latest release, 1.65.0, was published on Oct 2, 2026. On PyPI it is downloaded about 4.7M times per week. ### Alternatives - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) - [PyGWalker](https://awesomedataviz.com/tools/pygwalker/): Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker. (16K stars) ### Comparisons - [Dash vs Streamlit](https://awesomedataviz.com/compare/dash-vs-streamlit/) - [Matplotlib vs Streamlit](https://awesomedataviz.com/compare/matplotlib-vs-streamlit/) - [Bokeh vs Streamlit](https://awesomedataviz.com/compare/bokeh-vs-streamlit/) - [Streamlit vs Taipy](https://awesomedataviz.com/compare/streamlit-vs-taipy/) - [Shiny vs Streamlit](https://awesomedataviz.com/compare/shiny-vs-streamlit/) - [Plotly (Python) vs Streamlit](https://awesomedataviz.com/compare/plotly-python-vs-streamlit/) - [Panel vs Streamlit](https://awesomedataviz.com/compare/panel-vs-streamlit/) - [Shiny for Python vs Streamlit](https://awesomedataviz.com/compare/shiny-for-python-vs-streamlit/) Source: https://awesomedataviz.com/tools/streamlit/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Leaflet > JavaScript library for mobile-friendly interactive maps. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://leafletjs.com - Repository: https://github.com/Leaflet/Leaflet - License: BSD-2-Clause - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 45,702 - Commits in the last 12 months: 184 - Contributors: 382 - Last commit: Sep 19, 2026 - Latest release: v1.9.4 (May 18, 2023) - Install (npm): `npm install leaflet`, 9.3M downloads per week - Topics: Maps & geospatial visualization ### Overview Leaflet is an open-source JavaScript mapping library released under the BSD-2-Clause license. Its GitHub repository has 45,702 stars, 6,179 forks, and 382 contributors. It is actively developed with 184 commits in the last 12 months. The latest release, v1.9.4, was published on May 18, 2023. On npm it is downloaded about 9.3M times per week. ### Alternatives - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) - [Potree](https://awesomedataviz.com/tools/potree/): WebGL point cloud viewer for large datasets such as LiDAR scans. (5.6K stars) ### Comparisons - [Cesium vs Leaflet](https://awesomedataviz.com/compare/cesium-vs-leaflet/) - [Deck.gl vs Leaflet](https://awesomedataviz.com/compare/deck-gl-vs-leaflet/) - [Leaflet vs OpenLayers](https://awesomedataviz.com/compare/leaflet-vs-openlayers/) - [Leaflet vs MapLibre GL JS](https://awesomedataviz.com/compare/leaflet-vs-maplibre-gl-js/) Source: https://awesomedataviz.com/tools/leaflet/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Diagrams > Diagram as code in Python for prototyping cloud system architectures. - Category: [Diagrams as code](https://awesomedataviz.com/categories/diagrams-as-code/) - Website: https://diagrams.mingrammer.com - Repository: https://github.com/mingrammer/diagrams - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 42,673 - Commits in the last 12 months: 48 - Contributors: 178 - Last commit: Oct 1, 2026 - Latest release: v0.25.1 (Nov 22, 2025) - Install (PyPI): `pip install diagrams`, 217.5K downloads per week - Topics: Diagrams & diagrams as code ### Overview Diagrams is an open-source diagram-as-code tool released under the MIT license. Its GitHub repository has 42,673 stars, 2,732 forks, and 178 contributors. It is actively developed with 48 commits in the last 12 months. The latest release, v0.25.1, was published on Nov 22, 2025. On PyPI it is downloaded about 217.5K times per week. ### Alternatives - [Mermaid](https://awesomedataviz.com/tools/mermaid/): Generate diagrams and flowcharts from markdown-like text definitions, with a live editor. (90.5K stars) - [D2](https://awesomedataviz.com/tools/d2/): Declarative diagram scripting language that turns text into diagrams. (25.6K stars) - [PlantUML](https://awesomedataviz.com/tools/plantuml/): Generates UML, Gantt, mind map and other diagrams from plain text. (13.4K stars) - [Markmap](https://awesomedataviz.com/tools/markmap/): Builds interactive mind maps from Markdown. (13.1K stars) - [flowchart.js](https://awesomedataviz.com/tools/flowchart-js/): Draws SVG flowcharts from a textual description. (8.7K stars) - [Penrose](https://awesomedataviz.com/tools/penrose/): Creates diagrams from mathematical notation in plain text, from Carnegie Mellon University. (8K stars) ### Comparisons - [Diagrams vs Mermaid](https://awesomedataviz.com/compare/diagrams-vs-mermaid/) - [D2 vs Diagrams](https://awesomedataviz.com/compare/d2-vs-diagrams/) - [Diagrams vs PlantUML](https://awesomedataviz.com/compare/diagrams-vs-plantuml/) - [Diagrams vs Markmap](https://awesomedataviz.com/compare/diagrams-vs-markmap/) Source: https://awesomedataviz.com/tools/diagrams/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## xyflow > React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Website: https://xyflow.com - Repository: https://github.com/xyflow/xyflow - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 38,582 - Commits in the last 12 months: 510 - Contributors: 138 - Last commit: Sep 24, 2026 - Latest release: @xyflow/svelte@1.7.0 (Sep 24, 2026) - Install (npm): `npm install @xyflow/react`, 15.2M downloads per week - Topics: Graph & network visualization, Diagrams & diagrams as code ### Overview xyflow is an open-source JavaScript graph visualization library released under the MIT license. Its GitHub repository has 38,582 stars, 2,541 forks, and 138 contributors. It is actively developed with 510 commits in the last 12 months. The latest release, @xyflow/svelte@1.7.0, was published on Sep 24, 2026. On npm it is downloaded about 15.2M times per week. ### Alternatives - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) - [3d-force-graph](https://awesomedataviz.com/tools/3d-force-graph/): 3D force-directed graph component using Three.js/WebGL. (6.4K stars) ### Comparisons - [G6 vs xyflow](https://awesomedataviz.com/compare/g6-vs-xyflow/) - [Sigma.js vs xyflow](https://awesomedataviz.com/compare/sigma-js-vs-xyflow/) - [Cytoscape.js vs xyflow](https://awesomedataviz.com/compare/cytoscape-js-vs-xyflow/) - [Vue Flow vs xyflow](https://awesomedataviz.com/compare/vue-flow-vs-xyflow/) Source: https://awesomedataviz.com/tools/xyflow/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## MPAndroidChart > A powerful & easy to use chart library. - Category: [Android chart libraries](https://awesomedataviz.com/categories/android/) - Website: https://philjay.cc/mpandroidchart - Repository: https://github.com/PhilJay/MPAndroidChart - License: Apache-2.0 - Language: Kotlin - Status: Active (commits in the last 90 days) - GitHub stars: 38,183 - Commits in the last 12 months: 20 - Contributors: 64 - Last commit: Sep 28, 2026 - Latest release: v4.0.1 (Sep 28, 2026) - Topics: Financial & stock charts ### Overview MPAndroidChart is an open-source Android chart library released under the Apache-2.0 license. Its GitHub repository has 38,183 stars, 8,975 forks, and 64 contributors. It is actively developed with 20 commits in the last 12 months. The latest release, v4.0.1, was published on Sep 28, 2026. ### Alternatives - [HelloCharts](https://awesomedataviz.com/tools/hellocharts/): Android chart library with line, column, pie, bubble and combo charts, plus zoom and scroll. (7.6K stars) - [WilliamChart](https://awesomedataviz.com/tools/williamchart/): Simple chart library. (5.1K stars) - [Vico](https://awesomedataviz.com/tools/vico/): Extensible chart library for Jetpack Compose and Compose Multiplatform. (3.2K stars) - [DecoView](https://awesomedataviz.com/tools/decoview/): Animated circular wheel chart library. (984 stars) ### Comparisons - [HelloCharts vs MPAndroidChart](https://awesomedataviz.com/compare/hellocharts-vs-mpandroidchart/) - [MPAndroidChart vs WilliamChart](https://awesomedataviz.com/compare/mpandroidchart-vs-williamchart/) - [MPAndroidChart vs Vico](https://awesomedataviz.com/compare/mpandroidchart-vs-vico/) - [DecoView vs MPAndroidChart](https://awesomedataviz.com/compare/decoview-vs-mpandroidchart/) Source: https://awesomedataviz.com/tools/mpandroidchart/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Netron > Viewer for neural network, deep learning and machine learning models. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Website: https://netron.app - Repository: https://github.com/lutzroeder/netron - License: MIT - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 33,544 - Commits in the last 12 months: 926 - Contributors: 1 - Last commit: Oct 3, 2026 - Latest release: v9.3.1 (Oct 2, 2026) - Install (PyPI): `pip install netron`, 16.1K downloads per week - Topics: Machine learning & AI visualization ### Overview Netron is an open-source ML visualization tool released under the MIT license. Its GitHub repository has 33,544 stars, 3,185 forks, and 1 contributor. It is actively developed with 926 commits in the last 12 months. The latest release, v9.3.1, was published on Oct 2, 2026. On PyPI it is downloaded about 16.1K times per week. ### Alternatives - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) - [BertViz](https://awesomedataviz.com/tools/bertviz/): Visualize attention in Transformer language models such as BERT and GPT-2. (8.2K stars) ### Comparisons - [Netron vs PlotNeuralNet](https://awesomedataviz.com/compare/netron-vs-plotneuralnet/) - [Netron vs Opik](https://awesomedataviz.com/compare/netron-vs-opik/) - [Netron vs Phoenix](https://awesomedataviz.com/compare/netron-vs-phoenix/) - [FiftyOne vs Netron](https://awesomedataviz.com/compare/fiftyone-vs-netron/) Source: https://awesomedataviz.com/tools/netron/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Redash > Query data sources with SQL, then visualize the results and build dashboards. - Category: [Open-source dashboards & BI tools](https://awesomedataviz.com/categories/dashboards-and-bi/) - Website: http://redash.io/ - Repository: https://github.com/getredash/redash - License: BSD-2-Clause - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 28,833 - Commits in the last 12 months: 90 - Contributors: 392 - Last commit: Oct 3, 2026 - Latest release: v26.9.0 (Sep 24, 2026) - Topics: Dashboards & BI ### Overview Redash is an open-source dashboard and BI tool released under the BSD-2-Clause license. Its GitHub repository has 28,833 stars, 4,631 forks, and 392 contributors. It is actively developed with 90 commits in the last 12 months. The latest release, v26.9.0, was published on Sep 24, 2026. ### Alternatives - [Grafana](https://awesomedataviz.com/tools/grafana/): Observability and data visualization platform for metrics, logs and traces from many data sources. (77.1K stars) - [Apache Superset](https://awesomedataviz.com/tools/superset/): Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. (75K stars) - [Metabase](https://awesomedataviz.com/tools/metabase/): Business intelligence tool for querying data and building dashboards, with embedded analytics. (49.5K stars) - [Kibana](https://awesomedataviz.com/tools/kibana/): Visualization and dashboard UI for data stored in Elasticsearch. (21.3K stars) - [Evidence](https://awesomedataviz.com/tools/evidence/): Business intelligence as code: build reports and dashboards with SQL and Markdown. (7K stars) - [Lightdash](https://awesomedataviz.com/tools/lightdash/): BI tool that turns dbt projects into metrics, charts and dashboards. (6.2K stars) ### Comparisons - [Grafana vs Redash](https://awesomedataviz.com/compare/grafana-vs-redash/) - [Redash vs Apache Superset](https://awesomedataviz.com/compare/redash-vs-superset/) - [Metabase vs Redash](https://awesomedataviz.com/compare/metabase-vs-redash/) - [Kibana vs Redash](https://awesomedataviz.com/compare/kibana-vs-redash/) Source: https://awesomedataviz.com/tools/redash/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Charts > IOS port of MPAndroidChart. You can create charts for both platforms with very similar code. - Category: [iOS & Swift chart libraries](https://awesomedataviz.com/categories/ios/) - Repository: https://github.com/ChartsOrg/Charts - License: Apache-2.0 - Language: Swift - Status: Maintained (commits in the last 12 months) - GitHub stars: 27,997 - Commits in the last 12 months: 1 - Contributors: 151 - Last commit: Mar 4, 2026 - Latest release: 5.1.0 (Feb 16, 2024) ### Overview Charts is an open-source iOS chart library released under the Apache-2.0 license. Its GitHub repository has 27,997 stars, 5,989 forks, and 151 contributors. It is maintained with 1 commit in the last 12 months; the most recent commit was on Mar 4, 2026. The latest release, 5.1.0, was published on Feb 16, 2024. ### Alternatives - [PNChart](https://awesomedataviz.com/tools/pnchart/): A simple and beautiful chart lib used in Piner and CoinsMan. (9.6K stars) - [ChartView](https://awesomedataviz.com/tools/chartview/): Line, bar and pie chart views built with SwiftUI. (5.6K stars) - [JBChartView](https://awesomedataviz.com/tools/jbchartview/): Charting library for both line and bar graphs. (3.7K stars) - [Core Plot](https://awesomedataviz.com/tools/core-plot/): 2D plotting framework for macOS, iOS and tvOS. (2.8K stars) - [BEMSimpleLineGraph](https://awesomedataviz.com/tools/bemsimplelinegraph/): Highly customizable and interactive line graphs. (2.6K stars) - [SwiftCharts](https://awesomedataviz.com/tools/swiftcharts/): Customizable charts library for iOS. (2.6K stars) ### Comparisons - [Charts vs PNChart](https://awesomedataviz.com/compare/charts-vs-pnchart/) - [Charts vs ChartView](https://awesomedataviz.com/compare/charts-vs-chartview/) - [Charts vs JBChartView](https://awesomedataviz.com/compare/charts-vs-jbchartview/) - [Charts vs Core Plot](https://awesomedataviz.com/compare/charts-vs-core-plot/) Source: https://awesomedataviz.com/tools/charts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Recharts > Declarative react components to render D3 charts. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://recharts.github.io - Repository: https://github.com/recharts/recharts - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 27,612 - Commits in the last 12 months: 1,046 - Contributors: 412 - Last commit: Oct 4, 2026 - Latest release: v3.10.1 (Jul 25, 2026) - Install (npm): `npm install recharts`, 70.7M downloads per week ### Overview Recharts is an open-source React chart library released under the MIT license. Its GitHub repository has 27,612 stars, 1,999 forks, and 412 contributors. It is actively developed with 1,046 commits in the last 12 months. The latest release, v3.10.1, was published on Jul 25, 2026. On npm it is downloaded about 70.7M times per week. ### Alternatives - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) - [react-chartjs-2](https://awesomedataviz.com/tools/react-chartjs-2/): React components for Chart.js. (6.9K stars) ### Comparisons - [Recharts vs visx](https://awesomedataviz.com/compare/recharts-vs-visx/) - [Recharts vs Tremor](https://awesomedataviz.com/compare/recharts-vs-tremor/) - [nivo vs Recharts](https://awesomedataviz.com/compare/nivo-vs-recharts/) - [Recharts vs Victory](https://awesomedataviz.com/compare/recharts-vs-victory/) - [Chart.js vs Recharts](https://awesomedataviz.com/compare/chart-js-vs-recharts/) Source: https://awesomedataviz.com/tools/recharts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## D2 > Declarative diagram scripting language that turns text into diagrams. - Category: [Diagrams as code](https://awesomedataviz.com/categories/diagrams-as-code/) - Website: https://d2lang.com - Repository: https://github.com/d2lang/d2 - License: MPL-2.0 - Language: Go - Status: Active (commits in the last 90 days) - GitHub stars: 25,564 - Commits in the last 12 months: 324 - Contributors: 65 - Last commit: Oct 2, 2026 - Latest release: v0.9.0 (Sep 7, 2026) - Install (Go): `go get github.com/d2lang/d2` - Topics: Diagrams & diagrams as code ### Overview D2 is an open-source diagram-as-code tool released under the MPL-2.0 license. Its GitHub repository has 25,564 stars, 757 forks, and 65 contributors. It is actively developed with 324 commits in the last 12 months. The latest release, v0.9.0, was published on Sep 7, 2026. ### Alternatives - [Mermaid](https://awesomedataviz.com/tools/mermaid/): Generate diagrams and flowcharts from markdown-like text definitions, with a live editor. (90.5K stars) - [Diagrams](https://awesomedataviz.com/tools/diagrams/): Diagram as code in Python for prototyping cloud system architectures. (42.7K stars) - [PlantUML](https://awesomedataviz.com/tools/plantuml/): Generates UML, Gantt, mind map and other diagrams from plain text. (13.4K stars) - [Markmap](https://awesomedataviz.com/tools/markmap/): Builds interactive mind maps from Markdown. (13.1K stars) - [flowchart.js](https://awesomedataviz.com/tools/flowchart-js/): Draws SVG flowcharts from a textual description. (8.7K stars) - [Penrose](https://awesomedataviz.com/tools/penrose/): Creates diagrams from mathematical notation in plain text, from Carnegie Mellon University. (8K stars) ### Comparisons - [D2 vs Mermaid](https://awesomedataviz.com/compare/d2-vs-mermaid/) - [D2 vs Diagrams](https://awesomedataviz.com/compare/d2-vs-diagrams/) - [D2 vs PlantUML](https://awesomedataviz.com/compare/d2-vs-plantuml/) - [D2 vs Markmap](https://awesomedataviz.com/compare/d2-vs-markmap/) Source: https://awesomedataviz.com/tools/d2/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## PlotNeuralNet > LaTeX code for drawing neural network architecture diagrams. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Repository: https://github.com/HarisIqbal88/PlotNeuralNet - License: MIT - Language: TeX - Status: Inactive (no commits in over a year) - GitHub stars: 25,009 - Commits in the last 12 months: 0 - Contributors: 10 - Last commit: Nov 6, 2020 - Latest release: v1.0.0 (Dec 25, 2018) - Topics: Diagrams & diagrams as code, Machine learning & AI visualization ### Overview PlotNeuralNet is an open-source ML visualization tool released under the MIT license. Its GitHub repository has 25,009 stars, 3,059 forks, and 10 contributors. It has not had a commit since Nov 6, 2020. The latest release, v1.0.0, was published on Dec 25, 2018. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) - [BertViz](https://awesomedataviz.com/tools/bertviz/): Visualize attention in Transformer language models such as BERT and GPT-2. (8.2K stars) ### Comparisons - [Netron vs PlotNeuralNet](https://awesomedataviz.com/compare/netron-vs-plotneuralnet/) - [Opik vs PlotNeuralNet](https://awesomedataviz.com/compare/opik-vs-plotneuralnet/) - [Phoenix vs PlotNeuralNet](https://awesomedataviz.com/compare/phoenix-vs-plotneuralnet/) - [FiftyOne vs PlotNeuralNet](https://awesomedataviz.com/compare/fiftyone-vs-plotneuralnet/) Source: https://awesomedataviz.com/tools/plotneuralnet/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Dash > Framework for building data apps and dashboards in Python, built on Plotly.js and React. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://plotly.com/dash - Repository: https://github.com/plotly/dash - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 24,441 - Commits in the last 12 months: 1,348 - Contributors: 196 - Last commit: Oct 2, 2026 - Latest release: v4.4.1 (Jul 21, 2026) - Install (PyPI): `pip install dash`, 1.7M downloads per week - Topics: Dashboards & BI ### Overview Dash is an open-source Python visualization library released under the MIT license. Its GitHub repository has 24,441 stars, 2,328 forks, and 196 contributors. It is actively developed with 1,348 commits in the last 12 months. The latest release, v4.4.1, was published on Jul 21, 2026. On PyPI it is downloaded about 1.7M times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) - [PyGWalker](https://awesomedataviz.com/tools/pygwalker/): Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker. (16K stars) ### Comparisons - [Dash vs Streamlit](https://awesomedataviz.com/compare/dash-vs-streamlit/) - [Dash vs Matplotlib](https://awesomedataviz.com/compare/dash-vs-matplotlib/) - [Bokeh vs Dash](https://awesomedataviz.com/compare/bokeh-vs-dash/) - [Dash vs Taipy](https://awesomedataviz.com/compare/dash-vs-taipy/) Source: https://awesomedataviz.com/tools/dash/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Matplotlib > 2D plotting library. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://matplotlib.org/ - Repository: https://github.com/matplotlib/matplotlib - License: PSF-2.0 - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 23,323 - Commits in the last 12 months: 2,023 - Contributors: 438 - Last commit: Oct 4, 2026 - Latest release: v3.11.2 (Sep 11, 2026) - Install (PyPI): `pip install matplotlib`, 39.5M downloads per week ### Overview Matplotlib is an open-source Python visualization library released under the PSF-2.0 license. Its GitHub repository has 23,323 stars, 8,503 forks, and 438 contributors. It is actively developed with 2,023 commits in the last 12 months. The latest release, v3.11.2, was published on Sep 11, 2026. On PyPI it is downloaded about 39.5M times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) - [PyGWalker](https://awesomedataviz.com/tools/pygwalker/): Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker. (16K stars) ### Comparisons - [Matplotlib vs Streamlit](https://awesomedataviz.com/compare/matplotlib-vs-streamlit/) - [Dash vs Matplotlib](https://awesomedataviz.com/compare/dash-vs-matplotlib/) - [Bokeh vs Matplotlib](https://awesomedataviz.com/compare/bokeh-vs-matplotlib/) - [Matplotlib vs Taipy](https://awesomedataviz.com/compare/matplotlib-vs-taipy/) - [ggplot2 vs Matplotlib](https://awesomedataviz.com/compare/ggplot2-vs-matplotlib/) Source: https://awesomedataviz.com/tools/matplotlib/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ChartDB > An Open-source tool to visualize database schemas and generate ER diagrams from a single query. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://chartdb.io - Repository: https://github.com/chartdb/chartdb - License: AGPL-3.0 - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 22,987 - Commits in the last 12 months: 116 - Contributors: 66 - Last commit: Apr 11, 2026 - Latest release: v1.20.1 (Apr 7, 2026) - Topics: Diagrams & diagrams as code ### Overview ChartDB is an open-source data visualization app released under the AGPL-3.0 license. Its GitHub repository has 22,987 stars, 1,494 forks, and 66 contributors. It is maintained with 116 commits in the last 12 months; the most recent commit was on Apr 11, 2026. The latest release, v1.20.1, was published on Apr 7, 2026. ### Alternatives - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) - [Kepler.gl](https://awesomedataviz.com/tools/kepler-gl/): Geospatial analysis tool for large-scale data sets. (12K stars) ### Comparisons - [ChartDB vs FlameGraph](https://awesomedataviz.com/compare/chartdb-vs-flamegraph/) - [ChartDB vs Data Formulator](https://awesomedataviz.com/compare/chartdb-vs-data-formulator/) - [ChartDB vs Sampler](https://awesomedataviz.com/compare/chartdb-vs-sampler/) - [ChartDB vs QGIS](https://awesomedataviz.com/compare/chartdb-vs-qgis/) Source: https://awesomedataviz.com/tools/chartdb/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Opik > Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Website: https://www.comet.com/docs/opik/ - Repository: https://github.com/comet-ml/opik - License: Apache-2.0 - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 22,373 - Commits in the last 12 months: 4,323 - Contributors: 159 - Last commit: Oct 2, 2026 - Latest release: 2.2.88 (Oct 2, 2026) - Install (PyPI): `pip install opik`, 424.8K downloads per week - Topics: Machine learning & AI visualization ### Overview Opik is an open-source ML visualization tool released under the Apache-2.0 license. Its GitHub repository has 22,373 stars, 1,841 forks, and 159 contributors. It is actively developed with 4,323 commits in the last 12 months. The latest release, 2.2.88, was published on Oct 2, 2026. On PyPI it is downloaded about 424.8K times per week. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) - [BertViz](https://awesomedataviz.com/tools/bertviz/): Visualize attention in Transformer language models such as BERT and GPT-2. (8.2K stars) ### Comparisons - [Netron vs Opik](https://awesomedataviz.com/compare/netron-vs-opik/) - [Opik vs PlotNeuralNet](https://awesomedataviz.com/compare/opik-vs-plotneuralnet/) - [Opik vs Phoenix](https://awesomedataviz.com/compare/opik-vs-phoenix/) - [FiftyOne vs Opik](https://awesomedataviz.com/compare/fiftyone-vs-opik/) Source: https://awesomedataviz.com/tools/opik/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Kibana > Visualization and dashboard UI for data stored in Elasticsearch. - Category: [Open-source dashboards & BI tools](https://awesomedataviz.com/categories/dashboards-and-bi/) - Website: https://www.elastic.co/products/kibana - Repository: https://github.com/elastic/kibana - License: Other - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 21,305 - Commits in the last 12 months: 21,018 - Contributors: 374 - Last commit: Oct 4, 2026 - Latest release: v9.5.4 (Sep 15, 2026) - Topics: Dashboards & BI ### Overview Kibana is a dashboard and BI tool. Its GitHub repository has 21,305 stars, 8,631 forks, and 374 contributors. It is actively developed with 21,018 commits in the last 12 months. The latest release, v9.5.4, was published on Sep 15, 2026. ### Alternatives - [Grafana](https://awesomedataviz.com/tools/grafana/): Observability and data visualization platform for metrics, logs and traces from many data sources. (77.1K stars) - [Apache Superset](https://awesomedataviz.com/tools/superset/): Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. (75K stars) - [Metabase](https://awesomedataviz.com/tools/metabase/): Business intelligence tool for querying data and building dashboards, with embedded analytics. (49.5K stars) - [Redash](https://awesomedataviz.com/tools/redash/): Query data sources with SQL, then visualize the results and build dashboards. (28.8K stars) - [Evidence](https://awesomedataviz.com/tools/evidence/): Business intelligence as code: build reports and dashboards with SQL and Markdown. (7K stars) - [Lightdash](https://awesomedataviz.com/tools/lightdash/): BI tool that turns dbt projects into metrics, charts and dashboards. (6.2K stars) ### Comparisons - [Grafana vs Kibana](https://awesomedataviz.com/compare/grafana-vs-kibana/) - [Kibana vs Apache Superset](https://awesomedataviz.com/compare/kibana-vs-superset/) - [Kibana vs Metabase](https://awesomedataviz.com/compare/kibana-vs-metabase/) - [Kibana vs Redash](https://awesomedataviz.com/compare/kibana-vs-redash/) Source: https://awesomedataviz.com/tools/kibana/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## visx > Low-level visualization components that combine D3 with React, by Airbnb. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://visx.airbnb.tech - Repository: https://github.com/airbnb/visx - License: MIT - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 21,075 - Commits in the last 12 months: 121 - Contributors: 161 - Last commit: Jun 22, 2026 - Latest release: v4.0.0 (Jun 11, 2026) - Install (npm): `npm install @visx/visx`, 118.6K downloads per week ### Overview visx is an open-source React chart library released under the MIT license. Its GitHub repository has 21,075 stars, 772 forks, and 161 contributors. It is maintained with 121 commits in the last 12 months; the most recent commit was on Jun 22, 2026. The latest release, v4.0.0, was published on Jun 11, 2026. On npm it is downloaded about 118.6K times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) - [react-chartjs-2](https://awesomedataviz.com/tools/react-chartjs-2/): React components for Chart.js. (6.9K stars) ### Comparisons - [Recharts vs visx](https://awesomedataviz.com/compare/recharts-vs-visx/) - [Tremor vs visx](https://awesomedataviz.com/compare/tremor-vs-visx/) - [nivo vs visx](https://awesomedataviz.com/compare/nivo-vs-visx/) - [Victory vs visx](https://awesomedataviz.com/compare/victory-vs-visx/) - [D3.js vs visx](https://awesomedataviz.com/compare/d3-vs-visx/) Source: https://awesomedataviz.com/tools/visx/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Bokeh > Interactive Web Plotting for Python. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://bokeh.org/ - Repository: https://github.com/bokeh/bokeh - License: BSD-3-Clause - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 20,455 - Commits in the last 12 months: 344 - Contributors: 389 - Last commit: Oct 3, 2026 - Install (PyPI): `pip install bokeh`, 1.3M downloads per week - Topics: Jupyter & notebook visualization ### Overview Bokeh is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 20,455 stars, 4,265 forks, and 389 contributors. It is actively developed with 344 commits in the last 12 months. On PyPI it is downloaded about 1.3M times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) - [PyGWalker](https://awesomedataviz.com/tools/pygwalker/): Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker. (16K stars) ### Comparisons - [Bokeh vs Streamlit](https://awesomedataviz.com/compare/bokeh-vs-streamlit/) - [Bokeh vs Dash](https://awesomedataviz.com/compare/bokeh-vs-dash/) - [Bokeh vs Matplotlib](https://awesomedataviz.com/compare/bokeh-vs-matplotlib/) - [Bokeh vs Taipy](https://awesomedataviz.com/compare/bokeh-vs-taipy/) Source: https://awesomedataviz.com/tools/bokeh/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## FlameGraph > Stack trace visualizer that generates interactive SVG flame graphs from profiling data. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: http://www.brendangregg.com/flamegraphs.html - Repository: https://github.com/brendangregg/FlameGraph - Language: Perl - Status: Inactive (no commits in over a year) - GitHub stars: 19,785 - Commits in the last 12 months: 0 - Contributors: 61 - Last commit: Oct 20, 2024 - Latest release: v1.0 (Aug 19, 2017) ### Overview FlameGraph is a data visualization app. Its GitHub repository has 19,785 stars, 2,110 forks, and 61 contributors. It has not had a commit since Oct 20, 2024. The latest release, v1.0, was published on Aug 19, 2017. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) - [Kepler.gl](https://awesomedataviz.com/tools/kepler-gl/): Geospatial analysis tool for large-scale data sets. (12K stars) ### Comparisons - [ChartDB vs FlameGraph](https://awesomedataviz.com/compare/chartdb-vs-flamegraph/) - [Data Formulator vs FlameGraph](https://awesomedataviz.com/compare/data-formulator-vs-flamegraph/) - [FlameGraph vs Sampler](https://awesomedataviz.com/compare/flamegraph-vs-sampler/) - [FlameGraph vs QGIS](https://awesomedataviz.com/compare/flamegraph-vs-qgis/) Source: https://awesomedataviz.com/tools/flamegraph/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Taipy > Python framework for building data and AI web applications with interactive charts and dashboards. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://www.taipy.io - Repository: https://github.com/Avaiga/taipy - License: Apache-2.0 - Language: Python - Status: Maintained (commits in the last 12 months) - GitHub stars: 19,443 - Commits in the last 12 months: 69 - Contributors: 78 - Last commit: May 7, 2026 - Latest release: 4.1.1 (Feb 16, 2026) - Install (PyPI): `pip install taipy`, 887 downloads per week - Topics: Dashboards & BI ### Overview Taipy is an open-source Python visualization library released under the Apache-2.0 license. Its GitHub repository has 19,443 stars, 1,992 forks, and 78 contributors. It is maintained with 69 commits in the last 12 months; the most recent commit was on May 7, 2026. The latest release, 4.1.1, was published on Feb 16, 2026. On PyPI it is downloaded about 887 times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) - [PyGWalker](https://awesomedataviz.com/tools/pygwalker/): Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker. (16K stars) ### Comparisons - [Streamlit vs Taipy](https://awesomedataviz.com/compare/streamlit-vs-taipy/) - [Dash vs Taipy](https://awesomedataviz.com/compare/dash-vs-taipy/) - [Matplotlib vs Taipy](https://awesomedataviz.com/compare/matplotlib-vs-taipy/) - [Bokeh vs Taipy](https://awesomedataviz.com/compare/bokeh-vs-taipy/) Source: https://awesomedataviz.com/tools/taipy/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Plotly (Python) > Interactive web based visualization built on top of plotly.js - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://plotly.com/python/ - Repository: https://github.com/plotly/plotly.py - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 18,822 - Commits in the last 12 months: 739 - Contributors: 303 - Last commit: Sep 24, 2026 - Latest release: v7.1.0 (Sep 15, 2026) - Install (PyPI): `pip install plotly`, 12.3M downloads per week - Topics: Jupyter & notebook visualization ### Overview Plotly (Python) is an open-source Python visualization library released under the MIT license. Its GitHub repository has 18,822 stars, 2,857 forks, and 303 contributors. It is actively developed with 739 commits in the last 12 months. The latest release, v7.1.0, was published on Sep 15, 2026. On PyPI it is downloaded about 12.3M times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [PyGWalker](https://awesomedataviz.com/tools/pygwalker/): Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker. (16K stars) ### Comparisons - [Plotly.js vs Plotly (Python)](https://awesomedataviz.com/compare/plotly-js-vs-plotly-python/) - [Plotly (Python) vs Streamlit](https://awesomedataviz.com/compare/plotly-python-vs-streamlit/) Source: https://awesomedataviz.com/tools/plotly-python/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Plotly.js > Powerful declarative library with support for 20 chart types. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://plotly.com/javascript/ - Repository: https://github.com/plotly/plotly.js - License: MIT - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 18,355 - Commits in the last 12 months: 1,549 - Contributors: 263 - Last commit: Oct 3, 2026 - Latest release: v4.1.1 (Sep 14, 2026) - Install (npm): `npm install plotly.js`, 873K downloads per week - Topics: GPU-accelerated & WebGL visualization ### Overview Plotly.js is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 18,355 stars, 2,044 forks, and 263 contributors. It is actively developed with 1,549 commits in the last 12 months. The latest release, v4.1.1, was published on Sep 14, 2026. On npm it is downloaded about 873K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) - [Chartist.js](https://awesomedataviz.com/tools/chartist-js/): Responsive charts with great browser compatibility. (13.4K stars) ### Comparisons - [Chart.js vs Plotly.js](https://awesomedataviz.com/compare/chart-js-vs-plotly-js/) - [Apache ECharts vs Plotly.js](https://awesomedataviz.com/compare/echarts-vs-plotly-js/) - [Lightweight Charts vs Plotly.js](https://awesomedataviz.com/compare/lightweight-charts-vs-plotly-js/) - [ApexCharts vs Plotly.js](https://awesomedataviz.com/compare/apexcharts-vs-plotly-js/) - [D3.js vs Plotly.js](https://awesomedataviz.com/compare/d3-vs-plotly-js/) - [Plotly.js vs Plotly (Python)](https://awesomedataviz.com/compare/plotly-js-vs-plotly-python/) Source: https://awesomedataviz.com/tools/plotly-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Data Formulator > AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://data-formulator.ai/ - Repository: https://github.com/microsoft/data-formulator - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 17,525 - Commits in the last 12 months: 930 - Contributors: 36 - Last commit: Aug 15, 2026 - Latest release: 0.8b1 (Aug 15, 2026) - Install (PyPI): `pip install data-formulator`, 331 downloads per week ### Overview Data Formulator is an open-source data visualization app released under the MIT license. Its GitHub repository has 17,525 stars, 1,724 forks, and 36 contributors. It is actively developed with 930 commits in the last 12 months. The latest release, 0.8b1, was published on Aug 15, 2026. On PyPI it is downloaded about 331 times per week. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) - [Kepler.gl](https://awesomedataviz.com/tools/kepler-gl/): Geospatial analysis tool for large-scale data sets. (12K stars) ### Comparisons - [ChartDB vs Data Formulator](https://awesomedataviz.com/compare/chartdb-vs-data-formulator/) - [Data Formulator vs FlameGraph](https://awesomedataviz.com/compare/data-formulator-vs-flamegraph/) - [Data Formulator vs Sampler](https://awesomedataviz.com/compare/data-formulator-vs-sampler/) - [Data Formulator vs QGIS](https://awesomedataviz.com/compare/data-formulator-vs-qgis/) Source: https://awesomedataviz.com/tools/data-formulator/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Lightweight Charts > Performant HTML5 canvas financial charts, from TradingView. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://www.tradingview.com/lightweight-charts/ - Repository: https://github.com/tradingview/lightweight-charts - License: Apache-2.0 - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 17,473 - Commits in the last 12 months: 329 - Contributors: 58 - Last commit: Oct 2, 2026 - Latest release: v5.2.1 (Aug 12, 2026) - Install (npm): `npm install lightweight-charts`, 1.4M downloads per week - Topics: Financial & stock charts ### Overview Lightweight Charts is an open-source JavaScript charting library released under the Apache-2.0 license. Its GitHub repository has 17,473 stars, 2,631 forks, and 58 contributors. It is actively developed with 329 commits in the last 12 months. The latest release, v5.2.1, was published on Aug 12, 2026. On npm it is downloaded about 1.4M times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) - [Chartist.js](https://awesomedataviz.com/tools/chartist-js/): Responsive charts with great browser compatibility. (13.4K stars) ### Comparisons - [Chart.js vs Lightweight Charts](https://awesomedataviz.com/compare/chart-js-vs-lightweight-charts/) - [Apache ECharts vs Lightweight Charts](https://awesomedataviz.com/compare/echarts-vs-lightweight-charts/) - [Lightweight Charts vs Plotly.js](https://awesomedataviz.com/compare/lightweight-charts-vs-plotly-js/) - [ApexCharts vs Lightweight Charts](https://awesomedataviz.com/compare/apexcharts-vs-lightweight-charts/) - [dxcharts-lite vs Lightweight Charts](https://awesomedataviz.com/compare/dxcharts-lite-vs-lightweight-charts/) Source: https://awesomedataviz.com/tools/lightweight-charts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Tremor > React components for building charts and dashboards, based on Recharts and Tailwind CSS. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://npm.tremor.so - Repository: https://github.com/tremorlabs/tremor-npm - License: Apache-2.0 - Language: TypeScript - Status: Inactive (no commits in over a year) - GitHub stars: 16,485 - Commits in the last 12 months: 0 - Contributors: 26 - Last commit: Jan 13, 2025 - Latest release: v3.18.7 (Jan 13, 2025) - Install (npm): `npm install @tremor/react`, 597.8K downloads per week - Topics: Dashboards & BI ### Overview Tremor is an open-source React chart library released under the Apache-2.0 license. Its GitHub repository has 16,485 stars, 478 forks, and 26 contributors. It has not had a commit since Jan 13, 2025. The latest release, v3.18.7, was published on Jan 13, 2025. On npm it is downloaded about 597.8K times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) - [react-chartjs-2](https://awesomedataviz.com/tools/react-chartjs-2/): React components for Chart.js. (6.9K stars) ### Comparisons - [Recharts vs Tremor](https://awesomedataviz.com/compare/recharts-vs-tremor/) - [Tremor vs visx](https://awesomedataviz.com/compare/tremor-vs-visx/) - [nivo vs Tremor](https://awesomedataviz.com/compare/nivo-vs-tremor/) - [Tremor vs Victory](https://awesomedataviz.com/compare/tremor-vs-victory/) Source: https://awesomedataviz.com/tools/tremor/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## react-native-maps > Map view component for iOS and Android in React Native. - Category: [React Native chart libraries](https://awesomedataviz.com/categories/react-native/) - Repository: https://github.com/react-native-maps/react-native-maps - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 16,004 - Commits in the last 12 months: 66 - Contributors: 424 - Last commit: Sep 27, 2026 - Latest release: v1.29.11 (Sep 27, 2026) - Install (npm): `npm install react-native-maps`, 1.4M downloads per week - Topics: Maps & geospatial visualization ### Overview react-native-maps is an open-source React Native chart library released under the MIT license. Its GitHub repository has 16,004 stars, 4,962 forks, and 424 contributors. It is actively developed with 66 commits in the last 12 months. The latest release, v1.29.11, was published on Sep 27, 2026. On npm it is downloaded about 1.4M times per week. ### Alternatives - [F2](https://awesomedataviz.com/tools/f2/): An elegant, interactive and flexible charting library for mobile, maintained by Alibaba (8K stars) - [React Native Chart Kit](https://awesomedataviz.com/tools/react-native-chart-kit/): Line, bar, pie, progress and contribution graph charts for React Native. (3.1K stars) - [react-native-graph](https://awesomedataviz.com/tools/react-native-graph/): Animated, high-performance line graphs for React Native, built with Skia. (2.6K stars) - [Victory Native](https://awesomedataviz.com/tools/victory-native/): High-performance charting library for React Native, built on React Native Skia. (1.2K stars) ### Comparisons - [F2 vs react-native-maps](https://awesomedataviz.com/compare/f2-vs-react-native-maps/) - [React Native Chart Kit vs react-native-maps](https://awesomedataviz.com/compare/react-native-chart-kit-vs-react-native-maps/) - [react-native-graph vs react-native-maps](https://awesomedataviz.com/compare/react-native-graph-vs-react-native-maps/) - [react-native-maps vs Victory Native](https://awesomedataviz.com/compare/react-native-maps-vs-victory-native/) Source: https://awesomedataviz.com/tools/react-native-maps/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## PyGWalker > Turns dataframes into a drag-and-drop visual analysis UI in Jupyter, based on Graphic Walker. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://kanaries.net/pygwalker - Repository: https://github.com/Kanaries/pygwalker - License: Apache-2.0 - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 15,983 - Commits in the last 12 months: 154 - Contributors: 26 - Last commit: Sep 5, 2026 - Latest release: 0.5.0.1 (Apr 4, 2026) - Install (PyPI): `pip install pygwalker`, 29K downloads per week - Topics: Jupyter & notebook visualization, Exploratory data analysis tools ### Overview PyGWalker is an open-source Python visualization library released under the Apache-2.0 license. Its GitHub repository has 15,983 stars, 889 forks, and 26 contributors. It is actively developed with 154 commits in the last 12 months. The latest release, 0.5.0.1, was published on Apr 4, 2026. On PyPI it is downloaded about 29K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/pygwalker/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Cesium > WebGL 3D globes and maps. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://cesium.com/cesiumjs/ - Repository: https://github.com/CesiumGS/cesium - License: Apache-2.0 - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 15,798 - Commits in the last 12 months: 3,159 - Contributors: 311 - Last commit: Oct 2, 2026 - Latest release: 1.146 (Oct 1, 2026) - Install (npm): `npm install cesium`, 570.1K downloads per week - Topics: Maps & geospatial visualization, GPU-accelerated & WebGL visualization ### Overview Cesium is an open-source JavaScript mapping library released under the Apache-2.0 license. Its GitHub repository has 15,798 stars, 3,882 forks, and 311 contributors. It is actively developed with 3,159 commits in the last 12 months. The latest release, 1.146, was published on Oct 1, 2026. On npm it is downloaded about 570.1K times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) - [Potree](https://awesomedataviz.com/tools/potree/): WebGL point cloud viewer for large datasets such as LiDAR scans. (5.6K stars) ### Comparisons - [Cesium vs Leaflet](https://awesomedataviz.com/compare/cesium-vs-leaflet/) - [Cesium vs Deck.gl](https://awesomedataviz.com/compare/cesium-vs-deck-gl/) - [Cesium vs OpenLayers](https://awesomedataviz.com/compare/cesium-vs-openlayers/) - [Cesium vs MapLibre GL JS](https://awesomedataviz.com/compare/cesium-vs-maplibre-gl-js/) Source: https://awesomedataviz.com/tools/cesium/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## blessed-contrib > Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Repository: https://github.com/yaronn/blessed-contrib - License: MIT - Language: JavaScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 15,775 - Commits in the last 12 months: 1 - Contributors: 45 - Last commit: May 1, 2026 - Install (npm): `npm install blessed-contrib`, 199.7K downloads per week - Topics: Terminal & command-line charts, Dashboards & BI ### Overview blessed-contrib is an open-source JavaScript visualization library released under the MIT license. Its GitHub repository has 15,775 stars, 835 forks, and 45 contributors. It is maintained with 1 commit in the last 12 months; the most recent commit was on May 1, 2026. On npm it is downloaded about 199.7K times per week. ### Alternatives - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) - [Vega-Lite](https://awesomedataviz.com/tools/vega-lite/): Is a high-level grammar of interactive graphics. It provides a concise JSON syntax for rapidly generating visualizations to support analysis. (5.5K stars) ### Comparisons - [blessed-contrib vs Vega](https://awesomedataviz.com/compare/blessed-contrib-vs-vega/) - [blessed-contrib vs Perspective](https://awesomedataviz.com/compare/blessed-contrib-vs-perspective/) - [blessed-contrib vs vue-echarts](https://awesomedataviz.com/compare/blessed-contrib-vs-vue-echarts/) - [blessed-contrib vs Textures.js](https://awesomedataviz.com/compare/blessed-contrib-vs-textures-js/) Source: https://awesomedataviz.com/tools/blessed-contrib/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## pyecharts > Python binding for Echarts library. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://pyecharts.org - Repository: https://github.com/pyecharts/pyecharts - License: MIT - Language: Python - Status: Maintained (commits in the last 12 months) - GitHub stars: 15,774 - Commits in the last 12 months: 2 - Contributors: 39 - Last commit: Feb 10, 2026 - Latest release: v2.1.0 (Feb 10, 2026) - Install (PyPI): `pip install pyecharts`, 144.9K downloads per week ### Overview pyecharts is an open-source Python visualization library released under the MIT license. Its GitHub repository has 15,774 stars, 2,843 forks, and 39 contributors. It is maintained with 2 commits in the last 12 months; the most recent commit was on Feb 10, 2026. The latest release, v2.1.0, was published on Feb 10, 2026. On PyPI it is downloaded about 144.9K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/pyecharts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ApexCharts > Modern & Interactive SVG Charts. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://apexcharts.com/ - Repository: https://github.com/apexcharts/apexcharts.js - License: Other - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 15,169 - Commits in the last 12 months: 832 - Contributors: 236 - Last commit: Oct 4, 2026 - Latest release: v7.8.0 (Oct 2, 2026) - Install (npm): `npm install apexcharts`, 2.5M downloads per week ### Overview ApexCharts is a JavaScript charting library. Its GitHub repository has 15,169 stars, 1,379 forks, and 236 contributors. It is actively developed with 832 commits in the last 12 months. The latest release, v7.8.0, was published on Oct 2, 2026. On npm it is downloaded about 2.5M times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) - [Chartist.js](https://awesomedataviz.com/tools/chartist-js/): Responsive charts with great browser compatibility. (13.4K stars) ### Comparisons - [ApexCharts vs Chart.js](https://awesomedataviz.com/compare/apexcharts-vs-chart-js/) - [ApexCharts vs Apache ECharts](https://awesomedataviz.com/compare/apexcharts-vs-echarts/) - [ApexCharts vs Plotly.js](https://awesomedataviz.com/compare/apexcharts-vs-plotly-js/) - [ApexCharts vs Lightweight Charts](https://awesomedataviz.com/compare/apexcharts-vs-lightweight-charts/) Source: https://awesomedataviz.com/tools/apexcharts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Frappe Charts > Simple, responsive SVG charts with zero dependencies. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://frappe.io/charts/docs - Repository: https://github.com/frappe/charts - License: MIT - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 15,088 - Commits in the last 12 months: 0 - Contributors: 47 - Last commit: Dec 12, 2024 - Latest release: v1.6.3 (Apr 27, 2022) - Install (npm): `npm install frappe-charts`, 103.3K downloads per week ### Overview Frappe Charts is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 15,088 stars, 752 forks, and 47 contributors. It has not had a commit since Dec 12, 2024. The latest release, v1.6.3, was published on Apr 27, 2022. On npm it is downloaded about 103.3K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Chartist.js](https://awesomedataviz.com/tools/chartist-js/): Responsive charts with great browser compatibility. (13.4K stars) Source: https://awesomedataviz.com/tools/frappe-charts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Sampler > Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://sampler.dev - Repository: https://github.com/sqshq/sampler - License: GPL-3.0 - Language: Go - Status: Inactive (no commits in over a year) - GitHub stars: 14,810 - Commits in the last 12 months: 0 - Contributors: 14 - Last commit: Oct 6, 2022 - Latest release: v1.1.0 (Dec 24, 2019) - Install (Go): `go get github.com/sqshq/sampler` - Topics: Terminal & command-line charts, Dashboards & BI ### Overview Sampler is an open-source data visualization app released under the GPL-3.0 license. Its GitHub repository has 14,810 stars, 667 forks, and 14 contributors. It has not had a commit since Oct 6, 2022. The latest release, v1.1.0, was published on Dec 24, 2019. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) - [Kepler.gl](https://awesomedataviz.com/tools/kepler-gl/): Geospatial analysis tool for large-scale data sets. (12K stars) ### Comparisons - [ChartDB vs Sampler](https://awesomedataviz.com/compare/chartdb-vs-sampler/) - [FlameGraph vs Sampler](https://awesomedataviz.com/compare/flamegraph-vs-sampler/) - [Data Formulator vs Sampler](https://awesomedataviz.com/compare/data-formulator-vs-sampler/) - [QGIS vs Sampler](https://awesomedataviz.com/compare/qgis-vs-sampler/) Source: https://awesomedataviz.com/tools/sampler/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Deck.gl > WebGL framework for visual exploratory data analysis of large datasets. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://deck.gl/ - Repository: https://github.com/visgl/deck.gl - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 14,623 - Commits in the last 12 months: 418 - Contributors: 288 - Last commit: Oct 4, 2026 - Latest release: v9.4.0 (Sep 5, 2026) - Install (npm): `npm install deck.gl`, 262.3K downloads per week - Topics: Maps & geospatial visualization, GPU-accelerated & WebGL visualization, Visualizing large datasets ### Overview Deck.gl is an open-source JavaScript mapping library released under the MIT license. Its GitHub repository has 14,623 stars, 2,275 forks, and 288 contributors. It is actively developed with 418 commits in the last 12 months. The latest release, v9.4.0, was published on Sep 5, 2026. On npm it is downloaded about 262.3K times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) - [Potree](https://awesomedataviz.com/tools/potree/): WebGL point cloud viewer for large datasets such as LiDAR scans. (5.6K stars) ### Comparisons - [Deck.gl vs Leaflet](https://awesomedataviz.com/compare/deck-gl-vs-leaflet/) - [Cesium vs Deck.gl](https://awesomedataviz.com/compare/cesium-vs-deck-gl/) - [Deck.gl vs OpenLayers](https://awesomedataviz.com/compare/deck-gl-vs-openlayers/) - [Deck.gl vs MapLibre GL JS](https://awesomedataviz.com/compare/deck-gl-vs-maplibre-gl-js/) - [Deck.gl vs Kepler.gl](https://awesomedataviz.com/compare/deck-gl-vs-kepler-gl/) Source: https://awesomedataviz.com/tools/deck-gl/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## QGIS > Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://qgis.org - Repository: https://github.com/qgis/QGIS - License: GPL-2.0 - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 14,461 - Commits in the last 12 months: 6,488 - Contributors: 343 - Last commit: Oct 2, 2026 - Latest release: final-3_44_15 (Sep 25, 2026) - Topics: Maps & geospatial visualization ### Overview QGIS is an open-source data visualization app released under the GPL-2.0 license. Its GitHub repository has 14,461 stars, 3,539 forks, and 343 contributors. It is actively developed with 6,488 commits in the last 12 months. The latest release, final-3_44_15, was published on Sep 25, 2026. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) - [Kepler.gl](https://awesomedataviz.com/tools/kepler-gl/): Geospatial analysis tool for large-scale data sets. (12K stars) ### Comparisons - [ChartDB vs QGIS](https://awesomedataviz.com/compare/chartdb-vs-qgis/) - [FlameGraph vs QGIS](https://awesomedataviz.com/compare/flamegraph-vs-qgis/) - [Data Formulator vs QGIS](https://awesomedataviz.com/compare/data-formulator-vs-qgis/) - [QGIS vs Sampler](https://awesomedataviz.com/compare/qgis-vs-sampler/) Source: https://awesomedataviz.com/tools/qgis/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## nivo > Supercharged dataviz components for React with isomorphic ability, demo. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://nivo.rocks - Repository: https://github.com/plouc/nivo - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 14,106 - Commits in the last 12 months: 24 - Contributors: 208 - Last commit: Jul 21, 2026 - Latest release: v0.99.0 (May 23, 2025) - Install (npm): `npm install @nivo/core`, 2M downloads per week ### Overview nivo is an open-source React chart library released under the MIT license. Its GitHub repository has 14,106 stars, 1,082 forks, and 208 contributors. It is actively developed with 24 commits in the last 12 months. The latest release, v0.99.0, was published on May 23, 2025. On npm it is downloaded about 2M times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) - [react-chartjs-2](https://awesomedataviz.com/tools/react-chartjs-2/): React components for Chart.js. (6.9K stars) ### Comparisons - [nivo vs Recharts](https://awesomedataviz.com/compare/nivo-vs-recharts/) - [nivo vs visx](https://awesomedataviz.com/compare/nivo-vs-visx/) - [nivo vs Tremor](https://awesomedataviz.com/compare/nivo-vs-tremor/) - [nivo vs Victory](https://awesomedataviz.com/compare/nivo-vs-victory/) Source: https://awesomedataviz.com/tools/nivo/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Seaborn > A library for making attractive and informative statistical graphics. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://seaborn.pydata.org/ - Repository: https://github.com/mwaskom/seaborn - License: BSD-3-Clause - Language: Python - Status: Maintained (commits in the last 12 months) - GitHub stars: 14,056 - Commits in the last 12 months: 18 - Contributors: 190 - Last commit: Jul 6, 2026 - Latest release: v0.13.2 (Jan 25, 2024) - Install (PyPI): `pip install seaborn`, 6.7M downloads per week ### Overview Seaborn is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 14,056 stars, 2,142 forks, and 190 contributors. It is maintained with 18 commits in the last 12 months; the most recent commit was on Jul 6, 2026. The latest release, v0.13.2, was published on Jan 25, 2024. On PyPI it is downloaded about 6.7M times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/seaborn/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ydata-profiling > Generates statistical analytic reports with visualization for quick data analysis (formerly pandas-profiling). - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://docs.sdk.ydata.ai - Repository: https://github.com/Data-Centric-AI-Community/fg-data-profiling - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 13,719 - Commits in the last 12 months: 8 - Contributors: 115 - Last commit: Sep 11, 2026 - Latest release: 4.20.0 (Sep 11, 2026) - Install (PyPI): `pip install ydata-profiling`, 158.5K downloads per week - Topics: Jupyter & notebook visualization, Exploratory data analysis tools ### Overview ydata-profiling is an open-source Python visualization library released under the MIT license. Its GitHub repository has 13,719 stars, 1,802 forks, and 115 contributors. It is actively developed with 8 commits in the last 12 months. The latest release, 4.20.0, was published on Sep 11, 2026. On PyPI it is downloaded about 158.5K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/ydata-profiling/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## termui > Terminal dashboard and widget library with charts, gauges, sparklines and more. - Category: [Go charting & plotting libraries](https://awesomedataviz.com/categories/go/) - Repository: https://github.com/gizak/termui - License: MIT - Language: Go - Status: Inactive (no commits in over a year) - GitHub stars: 13,590 - Commits in the last 12 months: 0 - Contributors: 43 - Last commit: Jul 10, 2025 - Install (Go): `go get github.com/gizak/termui/v3` - Topics: Terminal & command-line charts, Dashboards & BI ### Overview termui is an open-source Go plotting library released under the MIT license. Its GitHub repository has 13,590 stars, 820 forks, and 43 contributors. It has not had a commit since Jul 10, 2025. ### Alternatives - [go-echarts](https://awesomedataviz.com/tools/go-echarts/): Simple yet powerful data visualizing library for Go. (7.6K stars) - [go-diagrams](https://awesomedataviz.com/tools/go-diagrams/): Diagram-as-code library for system architecture diagrams in Go, rendered with Graphviz. (5.2K stars) - [asciigraph](https://awesomedataviz.com/tools/asciigraph/): Lightweight ASCII line graphs for command-line apps. (3.1K stars) - [termdash](https://awesomedataviz.com/tools/termdash/): Terminal-based dashboard library with line charts, bar charts, gauges and donuts. (3K stars) - [plot](https://awesomedataviz.com/tools/plot/): API for building and drawing plots in Go. (3K stars) - [svgo](https://awesomedataviz.com/tools/svgo/): Go Language Library for SVG generation. (2.3K stars) ### Comparisons - [go-echarts vs termui](https://awesomedataviz.com/compare/go-echarts-vs-termui/) - [go-diagrams vs termui](https://awesomedataviz.com/compare/go-diagrams-vs-termui/) - [asciigraph vs termui](https://awesomedataviz.com/compare/asciigraph-vs-termui/) - [termdash vs termui](https://awesomedataviz.com/compare/termdash-vs-termui/) Source: https://awesomedataviz.com/tools/termui/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Chartist.js > Responsive charts with great browser compatibility. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://gionkunz.github.io/chartist-js/ - Repository: https://github.com/chartist-js/chartist - License: MIT - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 13,390 - Commits in the last 12 months: 1 - Contributors: 65 - Last commit: Oct 18, 2025 - Latest release: v1.5.0 (Sep 30, 2025) - Install (npm): `npm install chartist`, 128K downloads per week ### Overview Chartist.js is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 13,390 stars, 2,465 forks, and 65 contributors. It is maintained with 1 commit in the last 12 months; the most recent commit was on Oct 18, 2025. The latest release, v1.5.0, was published on Sep 30, 2025. On npm it is downloaded about 128K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/chartist-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## PlantUML > Generates UML, Gantt, mind map and other diagrams from plain text. - Category: [Diagrams as code](https://awesomedataviz.com/categories/diagrams-as-code/) - Website: https://plantuml.com - Repository: https://github.com/plantuml/plantuml - License: LGPL-3.0 - Language: Java - Status: Active (commits in the last 90 days) - GitHub stars: 13,352 - Commits in the last 12 months: 846 - Contributors: 131 - Last commit: Oct 3, 2026 - Latest release: v1.2026.8 (Sep 5, 2026) - Install (Maven Central): `implementation("net.sourceforge.plantuml:plantuml:1.2025.4")` - Topics: Diagrams & diagrams as code ### Overview PlantUML is an open-source diagram-as-code tool released under the LGPL-3.0 license. Its GitHub repository has 13,352 stars, 1,235 forks, and 131 contributors. It is actively developed with 846 commits in the last 12 months. The latest release, v1.2026.8, was published on Sep 5, 2026. ### Alternatives - [Mermaid](https://awesomedataviz.com/tools/mermaid/): Generate diagrams and flowcharts from markdown-like text definitions, with a live editor. (90.5K stars) - [Diagrams](https://awesomedataviz.com/tools/diagrams/): Diagram as code in Python for prototyping cloud system architectures. (42.7K stars) - [D2](https://awesomedataviz.com/tools/d2/): Declarative diagram scripting language that turns text into diagrams. (25.6K stars) - [Markmap](https://awesomedataviz.com/tools/markmap/): Builds interactive mind maps from Markdown. (13.1K stars) - [flowchart.js](https://awesomedataviz.com/tools/flowchart-js/): Draws SVG flowcharts from a textual description. (8.7K stars) - [Penrose](https://awesomedataviz.com/tools/penrose/): Creates diagrams from mathematical notation in plain text, from Carnegie Mellon University. (8K stars) ### Comparisons - [Mermaid vs PlantUML](https://awesomedataviz.com/compare/mermaid-vs-plantuml/) - [Diagrams vs PlantUML](https://awesomedataviz.com/compare/diagrams-vs-plantuml/) - [D2 vs PlantUML](https://awesomedataviz.com/compare/d2-vs-plantuml/) - [Markmap vs PlantUML](https://awesomedataviz.com/compare/markmap-vs-plantuml/) Source: https://awesomedataviz.com/tools/plantuml/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Gource > Animated visualization of software version control history. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://gource.io - Repository: https://github.com/acaudwell/Gource - License: GPL-3.0 - Language: C++ - Status: Maintained (commits in the last 12 months) - GitHub stars: 13,159 - Commits in the last 12 months: 3 - Contributors: 39 - Last commit: Mar 6, 2026 - Latest release: gource-0.56 (Mar 6, 2026) ### Overview Gource is an open-source data visualization app released under the GPL-3.0 license. Its GitHub repository has 13,159 stars, 794 forks, and 39 contributors. It is maintained with 3 commits in the last 12 months; the most recent commit was on Mar 6, 2026. The latest release, gource-0.56, was published on Mar 6, 2026. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Kepler.gl](https://awesomedataviz.com/tools/kepler-gl/): Geospatial analysis tool for large-scale data sets. (12K stars) Source: https://awesomedataviz.com/tools/gource/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Markmap > Builds interactive mind maps from Markdown. - Category: [Diagrams as code](https://awesomedataviz.com/categories/diagrams-as-code/) - Website: https://markmap.js.org/ - Repository: https://github.com/markmap/markmap - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 13,147 - Commits in the last 12 months: 4 - Contributors: 12 - Last commit: Sep 12, 2026 - Latest release: v0.18.0 (Dec 19, 2024) - Install (npm): `npm install markmap-lib`, 152.1K downloads per week - Topics: Diagrams & diagrams as code ### Overview Markmap is an open-source diagram-as-code tool released under the MIT license. Its GitHub repository has 13,147 stars, 1,012 forks, and 12 contributors. It is actively developed with 4 commits in the last 12 months. The latest release, v0.18.0, was published on Dec 19, 2024. On npm it is downloaded about 152.1K times per week. ### Alternatives - [Mermaid](https://awesomedataviz.com/tools/mermaid/): Generate diagrams and flowcharts from markdown-like text definitions, with a live editor. (90.5K stars) - [Diagrams](https://awesomedataviz.com/tools/diagrams/): Diagram as code in Python for prototyping cloud system architectures. (42.7K stars) - [D2](https://awesomedataviz.com/tools/d2/): Declarative diagram scripting language that turns text into diagrams. (25.6K stars) - [PlantUML](https://awesomedataviz.com/tools/plantuml/): Generates UML, Gantt, mind map and other diagrams from plain text. (13.4K stars) - [flowchart.js](https://awesomedataviz.com/tools/flowchart-js/): Draws SVG flowcharts from a textual description. (8.7K stars) - [Penrose](https://awesomedataviz.com/tools/penrose/): Creates diagrams from mathematical notation in plain text, from Carnegie Mellon University. (8K stars) ### Comparisons - [Markmap vs Mermaid](https://awesomedataviz.com/compare/markmap-vs-mermaid/) - [Diagrams vs Markmap](https://awesomedataviz.com/compare/diagrams-vs-markmap/) - [D2 vs Markmap](https://awesomedataviz.com/compare/d2-vs-markmap/) - [Markmap vs PlantUML](https://awesomedataviz.com/compare/markmap-vs-plantuml/) Source: https://awesomedataviz.com/tools/markmap/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## G2 > An interactive and responsive charting library based on the grammar of graphics, maintained by Alibaba. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://g2.antv.antgroup.com - Repository: https://github.com/antvis/G2 - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 12,631 - Commits in the last 12 months: 88 - Contributors: 218 - Last commit: Sep 23, 2026 - Latest release: v5.4.8 (Jan 6, 2026) - Install (npm): `npm install @antv/g2`, 385.8K downloads per week - Topics: Grammar of graphics libraries ### Overview G2 is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 12,631 stars, 1,660 forks, and 218 contributors. It is actively developed with 88 commits in the last 12 months. The latest release, v5.4.8, was published on Jan 6, 2026. On npm it is downloaded about 385.8K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/g2/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## OpenLayers > Library for interactive web maps with support for many data sources, formats and projections. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://openlayers.org - Repository: https://github.com/openlayers/openlayers - License: BSD-2-Clause - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 12,602 - Commits in the last 12 months: 827 - Contributors: 332 - Last commit: Oct 2, 2026 - Latest release: v10.10.0 (Jul 27, 2026) - Install (npm): `npm install ol`, 923.1K downloads per week - Topics: Maps & geospatial visualization ### Overview OpenLayers is an open-source JavaScript mapping library released under the BSD-2-Clause license. Its GitHub repository has 12,602 stars, 3,193 forks, and 332 contributors. It is actively developed with 827 commits in the last 12 months. The latest release, v10.10.0, was published on Jul 27, 2026. On npm it is downloaded about 923.1K times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) - [Potree](https://awesomedataviz.com/tools/potree/): WebGL point cloud viewer for large datasets such as LiDAR scans. (5.6K stars) ### Comparisons - [Leaflet vs OpenLayers](https://awesomedataviz.com/compare/leaflet-vs-openlayers/) - [Cesium vs OpenLayers](https://awesomedataviz.com/compare/cesium-vs-openlayers/) - [Deck.gl vs OpenLayers](https://awesomedataviz.com/compare/deck-gl-vs-openlayers/) - [MapLibre GL JS vs OpenLayers](https://awesomedataviz.com/compare/maplibre-gl-js-vs-openlayers/) Source: https://awesomedataviz.com/tools/openlayers/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## G6 > Graph visualization library powered by Javascript & Typescript, maintained by Alibaba - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Website: https://g6.antv.antgroup.com/ - Repository: https://github.com/antvis/G6 - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 12,323 - Commits in the last 12 months: 44 - Contributors: 180 - Last commit: Sep 23, 2026 - Latest release: 5.1.1 (Apr 17, 2026) - Install (npm): `npm install @antv/g6`, 265.8K downloads per week - Topics: Graph & network visualization ### Overview G6 is an open-source JavaScript graph visualization library released under the MIT license. Its GitHub repository has 12,323 stars, 1,646 forks, and 180 contributors. It is actively developed with 44 commits in the last 12 months. The latest release, 5.1.1, was published on Apr 17, 2026. On npm it is downloaded about 265.8K times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) - [3d-force-graph](https://awesomedataviz.com/tools/3d-force-graph/): 3D force-directed graph component using Three.js/WebGL. (6.4K stars) ### Comparisons - [G6 vs xyflow](https://awesomedataviz.com/compare/g6-vs-xyflow/) - [G6 vs Sigma.js](https://awesomedataviz.com/compare/g6-vs-sigma-js/) - [Cytoscape.js vs G6](https://awesomedataviz.com/compare/cytoscape-js-vs-g6/) - [G6 vs Vue Flow](https://awesomedataviz.com/compare/g6-vs-vue-flow/) Source: https://awesomedataviz.com/tools/g6/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Sigma.js > JavaScript library dedicated to graph drawing. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Website: https://sigmajs.org/ - Repository: https://github.com/jacomyal/sigma.js - License: MIT - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 12,180 - Commits in the last 12 months: 6 - Contributors: 63 - Last commit: Apr 30, 2026 - Latest release: sigma@4.0.0-beta.6 (Sep 16, 2026) - Install (npm): `npm install sigma`, 518.4K downloads per week - Topics: Graph & network visualization, GPU-accelerated & WebGL visualization ### Overview Sigma.js is an open-source JavaScript graph visualization library released under the MIT license. Its GitHub repository has 12,180 stars, 1,616 forks, and 63 contributors. It is maintained with 6 commits in the last 12 months; the most recent commit was on Apr 30, 2026. The latest release, sigma@4.0.0-beta.6, was published on Sep 16, 2026. On npm it is downloaded about 518.4K times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) - [3d-force-graph](https://awesomedataviz.com/tools/3d-force-graph/): 3D force-directed graph component using Three.js/WebGL. (6.4K stars) ### Comparisons - [Sigma.js vs xyflow](https://awesomedataviz.com/compare/sigma-js-vs-xyflow/) - [G6 vs Sigma.js](https://awesomedataviz.com/compare/g6-vs-sigma-js/) - [Cytoscape.js vs Sigma.js](https://awesomedataviz.com/compare/cytoscape-js-vs-sigma-js/) - [Sigma.js vs Vue Flow](https://awesomedataviz.com/compare/sigma-js-vs-vue-flow/) Source: https://awesomedataviz.com/tools/sigma-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Kepler.gl > Geospatial analysis tool for large-scale data sets. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://kepler.gl/ - Repository: https://github.com/keplergl/kepler.gl - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 12,033 - Commits in the last 12 months: 402 - Contributors: 133 - Last commit: Oct 4, 2026 - Latest release: v3.3.0-alpha.15 (Sep 28, 2026) - Install (npm): `npm install @kepler.gl/components`, 23.5K downloads per week - Topics: Maps & geospatial visualization, Visualizing large datasets ### Overview Kepler.gl is an open-source data visualization app released under the MIT license. Its GitHub repository has 12,033 stars, 1,957 forks, and 133 contributors. It is actively developed with 402 commits in the last 12 months. The latest release, v3.3.0-alpha.15, was published on Sep 28, 2026. On npm it is downloaded about 23.5K times per week. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) ### Comparisons - [Deck.gl vs Kepler.gl](https://awesomedataviz.com/compare/deck-gl-vs-kepler-gl/) Source: https://awesomedataviz.com/tools/kepler-gl/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Vega > Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://vega.github.io/vega/ - Repository: https://github.com/vega/vega - License: BSD-3-Clause - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 12,008 - Commits in the last 12 months: 148 - Contributors: 150 - Last commit: Oct 2, 2026 - Latest release: v6.4.0 (Aug 14, 2026) - Install (npm): `npm install vega`, 1.4M downloads per week - Topics: Grammar of graphics libraries ### Overview Vega is an open-source JavaScript visualization library released under the BSD-3-Clause license. Its GitHub repository has 12,008 stars, 1,582 forks, and 150 contributors. It is actively developed with 148 commits in the last 12 months. The latest release, v6.4.0, was published on Aug 14, 2026. On npm it is downloaded about 1.4M times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) - [Vega-Lite](https://awesomedataviz.com/tools/vega-lite/): Is a high-level grammar of interactive graphics. It provides a concise JSON syntax for rapidly generating visualizations to support analysis. (5.5K stars) ### Comparisons - [blessed-contrib vs Vega](https://awesomedataviz.com/compare/blessed-contrib-vs-vega/) - [Perspective vs Vega](https://awesomedataviz.com/compare/perspective-vs-vega/) - [Vega vs vue-echarts](https://awesomedataviz.com/compare/vega-vs-vue-echarts/) - [Textures.js vs Vega](https://awesomedataviz.com/compare/textures-js-vs-vega/) Source: https://awesomedataviz.com/tools/vega/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## MapLibre GL JS > WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://maplibre.org/maplibre-gl-js/docs/ - Repository: https://github.com/maplibre/maplibre-gl-js - License: BSD-3-Clause - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 11,801 - Commits in the last 12 months: 1,416 - Contributors: 385 - Last commit: Oct 4, 2026 - Latest release: v6.12.0 (Oct 3, 2026) - Install (npm): `npm install maplibre-gl`, 6.8M downloads per week - Topics: Maps & geospatial visualization, GPU-accelerated & WebGL visualization ### Overview MapLibre GL JS is an open-source JavaScript mapping library released under the BSD-3-Clause license. Its GitHub repository has 11,801 stars, 1,268 forks, and 385 contributors. It is actively developed with 1,416 commits in the last 12 months. The latest release, v6.12.0, was published on Oct 3, 2026. On npm it is downloaded about 6.8M times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) - [Potree](https://awesomedataviz.com/tools/potree/): WebGL point cloud viewer for large datasets such as LiDAR scans. (5.6K stars) ### Comparisons - [Leaflet vs MapLibre GL JS](https://awesomedataviz.com/compare/leaflet-vs-maplibre-gl-js/) - [Cesium vs MapLibre GL JS](https://awesomedataviz.com/compare/cesium-vs-maplibre-gl-js/) - [Deck.gl vs MapLibre GL JS](https://awesomedataviz.com/compare/deck-gl-vs-maplibre-gl-js/) - [MapLibre GL JS vs OpenLayers](https://awesomedataviz.com/compare/maplibre-gl-js-vs-openlayers/) Source: https://awesomedataviz.com/tools/maplibre-gl-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Phoenix > ML observability in a notebook with UMAP visualizations - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Website: https://arize.com/docs/phoenix - Repository: https://github.com/Arize-ai/phoenix - License: Elastic-2.0 - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 11,704 - Commits in the last 12 months: 3,725 - Contributors: 235 - Last commit: Oct 3, 2026 - Latest release: arize-phoenix-v20.19.0 (Oct 1, 2026) - Install (PyPI): `pip install arize-phoenix`, 145.1K downloads per week - Topics: Jupyter & notebook visualization, Machine learning & AI visualization ### Overview Phoenix is an ML visualization tool. Its GitHub repository has 11,704 stars, 1,181 forks, and 235 contributors. It is actively developed with 3,725 commits in the last 12 months. The latest release, arize-phoenix-v20.19.0, was published on Oct 1, 2026. On PyPI it is downloaded about 145.1K times per week. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) - [BertViz](https://awesomedataviz.com/tools/bertviz/): Visualize attention in Transformer language models such as BERT and GPT-2. (8.2K stars) ### Comparisons - [Netron vs Phoenix](https://awesomedataviz.com/compare/netron-vs-phoenix/) - [Phoenix vs PlotNeuralNet](https://awesomedataviz.com/compare/phoenix-vs-plotneuralnet/) - [Opik vs Phoenix](https://awesomedataviz.com/compare/opik-vs-phoenix/) - [FiftyOne vs Phoenix](https://awesomedataviz.com/compare/fiftyone-vs-phoenix/) Source: https://awesomedataviz.com/tools/phoenix/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Rerun > An SDK for logging computer vision and robotics data paired with a visualizer for exploring that data over time. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://rerun.io/ - Repository: https://github.com/rerun-io/rerun - License: Apache-2.0 - Language: Rust - Status: Active (commits in the last 90 days) - GitHub stars: 11,543 - Commits in the last 12 months: 3,095 - Contributors: 188 - Last commit: Oct 2, 2026 - Latest release: 0.38.1 (Sep 17, 2026) - Install (PyPI): `pip install rerun-sdk`, 343.1K downloads per week - Install (crates.io): `cargo add rerun`, 523.5K downloads per 90 days - Topics: Time series & real-time charts, Machine learning & AI visualization ### Overview Rerun is an open-source Python visualization library released under the Apache-2.0 license. Its GitHub repository has 11,543 stars, 860 forks, and 188 contributors. It is actively developed with 3,095 commits in the last 12 months. The latest release, 0.38.1, was published on Sep 17, 2026. On PyPI it is downloaded about 343.1K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/rerun/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Perspective > Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://perspective-dev.github.io/ - Repository: https://github.com/perspective-dev/perspective - License: Apache-2.0 - Language: Rust - Status: Active (commits in the last 90 days) - GitHub stars: 11,270 - Commits in the last 12 months: 337 - Contributors: 89 - Last commit: Oct 3, 2026 - Latest release: v5.5.1 (Sep 18, 2026) - Install (npm): `npm install @finos/perspective`, 19.1K downloads per week - Topics: Dashboards & BI, Jupyter & notebook visualization, Time series & real-time charts ### Overview Perspective is an open-source JavaScript visualization library released under the Apache-2.0 license. Its GitHub repository has 11,270 stars, 1,344 forks, and 89 contributors. It is actively developed with 337 commits in the last 12 months. The latest release, v5.5.1, was published on Sep 18, 2026. On npm it is downloaded about 19.1K times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) - [Vega-Lite](https://awesomedataviz.com/tools/vega-lite/): Is a high-level grammar of interactive graphics. It provides a concise JSON syntax for rapidly generating visualizations to support analysis. (5.5K stars) ### Comparisons - [blessed-contrib vs Perspective](https://awesomedataviz.com/compare/blessed-contrib-vs-perspective/) - [Perspective vs Vega](https://awesomedataviz.com/compare/perspective-vs-vega/) - [Perspective vs vue-echarts](https://awesomedataviz.com/compare/perspective-vs-vue-echarts/) - [Perspective vs Textures.js](https://awesomedataviz.com/compare/perspective-vs-textures-js/) Source: https://awesomedataviz.com/tools/perspective/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Victory > Composable components for building interactive data visualizations - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://formidable.com/open-source/victory/ - Repository: https://github.com/FormidableLabs/victory - License: MIT - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 11,238 - Commits in the last 12 months: 3 - Contributors: 184 - Last commit: Dec 19, 2025 - Latest release: v37.3.6 (Jan 14, 2025) - Install (npm): `npm install victory`, 542.1K downloads per week ### Overview Victory is an open-source React chart library released under the MIT license. Its GitHub repository has 11,238 stars, 535 forks, and 184 contributors. It is maintained with 3 commits in the last 12 months; the most recent commit was on Dec 19, 2025. The latest release, v37.3.6, was published on Jan 14, 2025. On npm it is downloaded about 542.1K times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) - [react-chartjs-2](https://awesomedataviz.com/tools/react-chartjs-2/): React components for Chart.js. (6.9K stars) ### Comparisons - [Recharts vs Victory](https://awesomedataviz.com/compare/recharts-vs-victory/) - [Victory vs visx](https://awesomedataviz.com/compare/victory-vs-visx/) - [Tremor vs Victory](https://awesomedataviz.com/compare/tremor-vs-victory/) - [nivo vs Victory](https://awesomedataviz.com/compare/nivo-vs-victory/) Source: https://awesomedataviz.com/tools/victory/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Cytoscape.js > JavaScript library for graph drawing maintained by Cytoscape core developers. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Website: https://js.cytoscape.org/ - Repository: https://github.com/cytoscape/cytoscape.js - License: MIT - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 11,232 - Commits in the last 12 months: 185 - Contributors: 139 - Last commit: Sep 7, 2026 - Latest release: v3.34.3 (Sep 7, 2026) - Install (npm): `npm install cytoscape`, 20.2M downloads per week - Topics: Graph & network visualization ### Overview Cytoscape.js is an open-source JavaScript graph visualization library released under the MIT license. Its GitHub repository has 11,232 stars, 1,674 forks, and 139 contributors. It is actively developed with 185 commits in the last 12 months. The latest release, v3.34.3, was published on Sep 7, 2026. On npm it is downloaded about 20.2M times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) - [3d-force-graph](https://awesomedataviz.com/tools/3d-force-graph/): 3D force-directed graph component using Three.js/WebGL. (6.4K stars) ### Comparisons - [Cytoscape.js vs xyflow](https://awesomedataviz.com/compare/cytoscape-js-vs-xyflow/) - [Cytoscape.js vs G6](https://awesomedataviz.com/compare/cytoscape-js-vs-g6/) - [Cytoscape.js vs Sigma.js](https://awesomedataviz.com/compare/cytoscape-js-vs-sigma-js/) - [Cytoscape.js vs Vue Flow](https://awesomedataviz.com/compare/cytoscape-js-vs-vue-flow/) Source: https://awesomedataviz.com/tools/cytoscape-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## FiftyOne > Tool for visualizing, curating and evaluating computer vision datasets and models. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Website: https://fiftyone.ai - Repository: https://github.com/voxel51/fiftyone - License: Apache-2.0 - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 11,143 - Commits in the last 12 months: 8,917 - Contributors: 170 - Last commit: Oct 3, 2026 - Latest release: v1.22.1 (Sep 29, 2026) - Install (PyPI): `pip install fiftyone`, 31.1K downloads per week - Topics: Machine learning & AI visualization ### Overview FiftyOne is an open-source ML visualization tool released under the Apache-2.0 license. Its GitHub repository has 11,143 stars, 833 forks, and 170 contributors. It is actively developed with 8,917 commits in the last 12 months. The latest release, v1.22.1, was published on Sep 29, 2026. On PyPI it is downloaded about 31.1K times per week. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) - [BertViz](https://awesomedataviz.com/tools/bertviz/): Visualize attention in Transformer language models such as BERT and GPT-2. (8.2K stars) ### Comparisons - [FiftyOne vs Netron](https://awesomedataviz.com/compare/fiftyone-vs-netron/) - [FiftyOne vs PlotNeuralNet](https://awesomedataviz.com/compare/fiftyone-vs-plotneuralnet/) - [FiftyOne vs Opik](https://awesomedataviz.com/compare/fiftyone-vs-opik/) - [FiftyOne vs Phoenix](https://awesomedataviz.com/compare/fiftyone-vs-phoenix/) Source: https://awesomedataviz.com/tools/fiftyone/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## vue-echarts > Vue.js component for Apache ECharts. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://vue-echarts.dev - Repository: https://github.com/ecomfe/vue-echarts - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 10,758 - Commits in the last 12 months: 805 - Contributors: 15 - Last commit: Sep 28, 2026 - Latest release: v8.3.1 (Sep 28, 2026) - Install (npm): `npm install vue-echarts`, 581.8K downloads per week ### Overview vue-echarts is an open-source JavaScript visualization library released under the MIT license. Its GitHub repository has 10,758 stars, 1,494 forks, and 15 contributors. It is actively developed with 805 commits in the last 12 months. The latest release, v8.3.1, was published on Sep 28, 2026. On npm it is downloaded about 581.8K times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) - [Vega-Lite](https://awesomedataviz.com/tools/vega-lite/): Is a high-level grammar of interactive graphics. It provides a concise JSON syntax for rapidly generating visualizations to support analysis. (5.5K stars) ### Comparisons - [blessed-contrib vs vue-echarts](https://awesomedataviz.com/compare/blessed-contrib-vs-vue-echarts/) - [Vega vs vue-echarts](https://awesomedataviz.com/compare/vega-vs-vue-echarts/) - [Perspective vs vue-echarts](https://awesomedataviz.com/compare/perspective-vs-vue-echarts/) - [Textures.js vs vue-echarts](https://awesomedataviz.com/compare/textures-js-vs-vue-echarts/) Source: https://awesomedataviz.com/tools/vue-echarts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## uPlot > Small, fast canvas-based charts for time series, lines, areas, OHLC and bars. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Repository: https://github.com/leeoniya/uPlot - License: MIT - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 10,542 - Commits in the last 12 months: 118 - Contributors: 49 - Last commit: Sep 28, 2026 - Latest release: 1.6.32 (Mar 14, 2025) - Install (npm): `npm install uplot`, 714.6K downloads per week - Topics: Financial & stock charts, Time series & real-time charts ### Overview uPlot is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 10,542 stars, 462 forks, and 49 contributors. It is actively developed with 118 commits in the last 12 months. The latest release, 1.6.32, was published on Mar 14, 2025. On npm it is downloaded about 714.6K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) ### Comparisons - [Chart.js vs uPlot](https://awesomedataviz.com/compare/chart-js-vs-uplot/) Source: https://awesomedataviz.com/tools/uplot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## WordCloud > Word cloud generator for Python. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://amueller.github.io/word_cloud - Repository: https://github.com/amueller/word_cloud - License: MIT - Language: Python - Status: Maintained (commits in the last 12 months) - GitHub stars: 10,536 - Commits in the last 12 months: 5 - Contributors: 66 - Last commit: Jan 22, 2026 - Latest release: 1.9.6 (Jan 22, 2026) - Install (PyPI): `pip install wordcloud`, 355.8K downloads per week ### Overview WordCloud is an open-source Python visualization library released under the MIT license. Its GitHub repository has 10,536 stars, 2,312 forks, and 66 contributors. It is maintained with 5 commits in the last 12 months; the most recent commit was on Jan 22, 2026. The latest release, 1.9.6, was published on Jan 22, 2026. On PyPI it is downloaded about 355.8K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/wordcloud/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Vega-Altair > Declarative statistical visualizations, based on Vega-Lite. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://altair-viz.github.io/ - Repository: https://github.com/vega/altair - License: BSD-3-Clause - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 10,491 - Commits in the last 12 months: 153 - Contributors: 183 - Last commit: Sep 27, 2026 - Latest release: v6.3.0 (Sep 15, 2026) - Install (PyPI): `pip install altair`, 9.2M downloads per week - Topics: Jupyter & notebook visualization, Grammar of graphics libraries ### Overview Vega-Altair is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 10,491 stars, 874 forks, and 183 contributors. It is actively developed with 153 commits in the last 12 months. The latest release, v6.3.0, was published on Sep 15, 2026. On PyPI it is downloaded about 9.2M times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) ### Comparisons - [Vega-Altair vs Vega-Lite](https://awesomedataviz.com/compare/altair-vs-vega-lite/) Source: https://awesomedataviz.com/tools/altair/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Visdom > Tool for real-time visualization and monitoring of live data such as ML experiments. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Website: https://visdom.dev - Repository: https://github.com/fossasia/visdom - License: Apache-2.0 - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 10,318 - Commits in the last 12 months: 548 - Contributors: 125 - Last commit: Oct 4, 2026 - Latest release: v0.3.0 (Sep 11, 2026) - Topics: Time series & real-time charts, Machine learning & AI visualization ### Overview Visdom is an open-source ML visualization tool released under the Apache-2.0 license. Its GitHub repository has 10,318 stars, 1,272 forks, and 125 contributors. It is actively developed with 548 commits in the last 12 months. The latest release, v0.3.0, was published on Sep 11, 2026. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [BertViz](https://awesomedataviz.com/tools/bertviz/): Visualize attention in Transformer language models such as BERT and GPT-2. (8.2K stars) Source: https://awesomedataviz.com/tools/visdom/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## PNChart > A simple and beautiful chart lib used in Piner and CoinsMan. - Category: [iOS & Swift chart libraries](https://awesomedataviz.com/categories/ios/) - Repository: https://github.com/kevinzhow/PNChart - License: MIT - Language: Objective-C - Status: Inactive (no commits in over a year) - GitHub stars: 9,634 - Commits in the last 12 months: 0 - Contributors: 63 - Last commit: Mar 7, 2018 - Latest release: 0.5 (May 5, 2014) ### Overview PNChart is an open-source iOS chart library released under the MIT license. Its GitHub repository has 9,634 stars, 1,735 forks, and 63 contributors. It has not had a commit since Mar 7, 2018. The latest release, 0.5, was published on May 5, 2014. ### Alternatives - [Charts](https://awesomedataviz.com/tools/charts/): IOS port of MPAndroidChart. You can create charts for both platforms with very similar code. (28K stars) - [ChartView](https://awesomedataviz.com/tools/chartview/): Line, bar and pie chart views built with SwiftUI. (5.6K stars) - [JBChartView](https://awesomedataviz.com/tools/jbchartview/): Charting library for both line and bar graphs. (3.7K stars) - [Core Plot](https://awesomedataviz.com/tools/core-plot/): 2D plotting framework for macOS, iOS and tvOS. (2.8K stars) - [BEMSimpleLineGraph](https://awesomedataviz.com/tools/bemsimplelinegraph/): Highly customizable and interactive line graphs. (2.6K stars) - [SwiftCharts](https://awesomedataviz.com/tools/swiftcharts/): Customizable charts library for iOS. (2.6K stars) ### Comparisons - [Charts vs PNChart](https://awesomedataviz.com/compare/charts-vs-pnchart/) - [ChartView vs PNChart](https://awesomedataviz.com/compare/chartview-vs-pnchart/) - [JBChartView vs PNChart](https://awesomedataviz.com/compare/jbchartview-vs-pnchart/) - [Core Plot vs PNChart](https://awesomedataviz.com/compare/core-plot-vs-pnchart/) Source: https://awesomedataviz.com/tools/pnchart/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## C3.js > D3-based reusable chart library. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: http://c3js.org - Repository: https://github.com/c3js/c3 - License: MIT - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 9,350 - Commits in the last 12 months: 18 - Contributors: 127 - Last commit: Sep 14, 2026 - Latest release: v0.7.20 (Aug 8, 2020) - Install (npm): `npm install c3`, 184.1K downloads per week ### Overview C3.js is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 9,350 stars, 1,359 forks, and 127 contributors. It is actively developed with 18 commits in the last 12 months. The latest release, v0.7.20, was published on Aug 8, 2020. On npm it is downloaded about 184.1K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/c3-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## VisiData > Terminal spreadsheet multitool for exploring and arranging tabular data, with basic plotting. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: http://visidata.org - Repository: https://github.com/saulpw/visidata - License: GPL-3.0 - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 9,317 - Commits in the last 12 months: 576 - Contributors: 115 - Last commit: Sep 29, 2026 - Latest release: v3.4 (Jul 1, 2026) - Install (PyPI): `pip install visidata`, 4.9K downloads per week - Topics: Terminal & command-line charts ### Overview VisiData is an open-source data visualization app released under the GPL-3.0 license. Its GitHub repository has 9,317 stars, 371 forks, and 115 contributors. It is actively developed with 576 commits in the last 12 months. The latest release, v3.4, was published on Jul 1, 2026. On PyPI it is downloaded about 4.9K times per week. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/visidata/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## SciencePlots > Matplotlib styles for scientific figures and journal publications. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Repository: https://github.com/garrettj403/SciencePlots - License: MIT - Language: Python - Status: Maintained (commits in the last 12 months) - GitHub stars: 9,270 - Commits in the last 12 months: 10 - Contributors: 13 - Last commit: Jun 23, 2026 - Latest release: 2.2.2 (Jun 23, 2026) - Install (PyPI): `pip install SciencePlots`, 22.4K downloads per week ### Overview SciencePlots is an open-source Python visualization library released under the MIT license. Its GitHub repository has 9,270 stars, 821 forks, and 13 contributors. It is maintained with 10 commits in the last 12 months; the most recent commit was on Jun 23, 2026. The latest release, 2.2.2, was published on Jun 23, 2026. On PyPI it is downloaded about 22.4K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/scienceplots/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## RAWGraphs > Create web visualizations from CSV or Excel files. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://rawgraphs.io - Repository: https://github.com/rawgraphs/rawgraphs-app - License: Apache-2.0 - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 9,033 - Commits in the last 12 months: 0 - Contributors: 16 - Last commit: Jan 28, 2025 - Latest release: v2.0.1 (Jan 26, 2024) ### Overview RAWGraphs is an open-source data visualization app released under the Apache-2.0 license. Its GitHub repository has 9,033 stars, 1,841 forks, and 16 contributors. It has not had a commit since Jan 28, 2025. The latest release, v2.0.1, was published on Jan 26, 2024. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/rawgraphs/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## React-vis > React components to build data visualizations. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://uber.github.io/react-vis - Repository: https://github.com/uber/react-vis - License: MIT - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 8,785 - Commits in the last 12 months: 0 - Contributors: 113 - Last commit: Dec 18, 2024 - Latest release: v1.11.7 (Apr 19, 2019) - Install (npm): `npm install react-vis`, 107K downloads per week ### Overview React-vis is an open-source React chart library released under the MIT license. Its GitHub repository has 8,785 stars, 833 forks, and 113 contributors. It has not had a commit since Dec 18, 2024. The latest release, v1.11.7, was published on Apr 19, 2019. On npm it is downloaded about 107K times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [react-chartjs-2](https://awesomedataviz.com/tools/react-chartjs-2/): React components for Chart.js. (6.9K stars) Source: https://awesomedataviz.com/tools/react-vis/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## flowchart.js > Draws SVG flowcharts from a textual description. - Category: [Diagrams as code](https://awesomedataviz.com/categories/diagrams-as-code/) - Website: http://flowchart.js.org/ - Repository: https://github.com/adrai/flowchart.js - License: MIT - Language: JavaScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 8,700 - Commits in the last 12 months: 1 - Contributors: 30 - Last commit: Jan 15, 2026 - Install (npm): `npm install flowchart.js`, 40.7K downloads per week - Topics: Diagrams & diagrams as code ### Overview flowchart.js is an open-source diagram-as-code tool released under the MIT license. Its GitHub repository has 8,700 stars, 1,197 forks, and 30 contributors. It is maintained with 1 commit in the last 12 months; the most recent commit was on Jan 15, 2026. On npm it is downloaded about 40.7K times per week. ### Alternatives - [Mermaid](https://awesomedataviz.com/tools/mermaid/): Generate diagrams and flowcharts from markdown-like text definitions, with a live editor. (90.5K stars) - [Diagrams](https://awesomedataviz.com/tools/diagrams/): Diagram as code in Python for prototyping cloud system architectures. (42.7K stars) - [D2](https://awesomedataviz.com/tools/d2/): Declarative diagram scripting language that turns text into diagrams. (25.6K stars) - [PlantUML](https://awesomedataviz.com/tools/plantuml/): Generates UML, Gantt, mind map and other diagrams from plain text. (13.4K stars) - [Markmap](https://awesomedataviz.com/tools/markmap/): Builds interactive mind maps from Markdown. (13.1K stars) - [Penrose](https://awesomedataviz.com/tools/penrose/): Creates diagrams from mathematical notation in plain text, from Carnegie Mellon University. (8K stars) Source: https://awesomedataviz.com/tools/flowchart-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## draw.io > Client-side JavaScript editor for flowcharts, network, UML and other diagrams. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://www.drawio.com - Repository: https://github.com/jgraph/drawio - License: Apache-2.0 - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 8,555 - Commits in the last 12 months: 65 - Contributors: 3 - Last commit: Oct 3, 2026 - Latest release: v32.0.2 (Oct 3, 2026) - Topics: Diagrams & diagrams as code ### Overview draw.io is an open-source data visualization app released under the Apache-2.0 license. Its GitHub repository has 8,555 stars, 1,289 forks, and 3 contributors. It is actively developed with 65 commits in the last 12 months. The latest release, v32.0.2, was published on Oct 3, 2026. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/draw-io/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## react-map-gl > React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: http://visgl.github.io/react-map-gl/ - Repository: https://github.com/visgl/react-map-gl - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 8,503 - Commits in the last 12 months: 20 - Contributors: 187 - Last commit: Sep 3, 2026 - Latest release: v8.1.3 (Sep 2, 2026) - Install (npm): `npm install react-map-gl`, 2.7M downloads per week - Topics: Maps & geospatial visualization, GPU-accelerated & WebGL visualization ### Overview react-map-gl is an open-source JavaScript mapping library released under the MIT license. Its GitHub repository has 8,503 stars, 1,348 forks, and 187 contributors. It is actively developed with 20 commits in the last 12 months. The latest release, v8.1.3, was published on Sep 2, 2026. On npm it is downloaded about 2.7M times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [Potree](https://awesomedataviz.com/tools/potree/): WebGL point cloud viewer for large datasets such as LiDAR scans. (5.6K stars) Source: https://awesomedataviz.com/tools/react-map-gl/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## BertViz > Visualize attention in Transformer language models such as BERT and GPT-2. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Repository: https://github.com/jessevig/bertviz - License: Apache-2.0 - Language: Python - Status: Maintained (commits in the last 12 months) - GitHub stars: 8,193 - Commits in the last 12 months: 1 - Contributors: 5 - Last commit: Jan 8, 2026 - Latest release: v1.4.1 (Jun 1, 2025) - Install (PyPI): `pip install bertviz`, 635 downloads per week - Topics: Machine learning & AI visualization ### Overview BertViz is an open-source ML visualization tool released under the Apache-2.0 license. Its GitHub repository has 8,193 stars, 888 forks, and 5 contributors. It is maintained with 1 commit in the last 12 months; the most recent commit was on Jan 8, 2026. The latest release, v1.4.1, was published on Jun 1, 2025. On PyPI it is downloaded about 635 times per week. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) Source: https://awesomedataviz.com/tools/bertviz/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## F2 > An elegant, interactive and flexible charting library for mobile, maintained by Alibaba - Category: [React Native chart libraries](https://awesomedataviz.com/categories/react-native/) - Website: https://f2.antv.antgroup.com/ - Repository: https://github.com/antvis/F2 - License: MIT - Language: JavaScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 7,997 - Commits in the last 12 months: 28 - Contributors: 46 - Last commit: Apr 7, 2026 - Latest release: v5.14.0 (Nov 10, 2025) - Install (npm): `npm install @antv/f2`, 8.5K downloads per week ### Overview F2 is an open-source React Native chart library released under the MIT license. Its GitHub repository has 7,997 stars, 637 forks, and 46 contributors. It is maintained with 28 commits in the last 12 months; the most recent commit was on Apr 7, 2026. The latest release, v5.14.0, was published on Nov 10, 2025. On npm it is downloaded about 8.5K times per week. ### Alternatives - [react-native-maps](https://awesomedataviz.com/tools/react-native-maps/): Map view component for iOS and Android in React Native. (16K stars) - [React Native Chart Kit](https://awesomedataviz.com/tools/react-native-chart-kit/): Line, bar, pie, progress and contribution graph charts for React Native. (3.1K stars) - [react-native-graph](https://awesomedataviz.com/tools/react-native-graph/): Animated, high-performance line graphs for React Native, built with Skia. (2.6K stars) - [Victory Native](https://awesomedataviz.com/tools/victory-native/): High-performance charting library for React Native, built on React Native Skia. (1.2K stars) ### Comparisons - [F2 vs react-native-maps](https://awesomedataviz.com/compare/f2-vs-react-native-maps/) - [F2 vs React Native Chart Kit](https://awesomedataviz.com/compare/f2-vs-react-native-chart-kit/) - [F2 vs react-native-graph](https://awesomedataviz.com/compare/f2-vs-react-native-graph/) - [F2 vs Victory Native](https://awesomedataviz.com/compare/f2-vs-victory-native/) Source: https://awesomedataviz.com/tools/f2/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Penrose > Creates diagrams from mathematical notation in plain text, from Carnegie Mellon University. - Category: [Diagrams as code](https://awesomedataviz.com/categories/diagrams-as-code/) - Website: https://penrose.cs.cmu.edu - Repository: https://github.com/penrose/penrose - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 7,985 - Commits in the last 12 months: 48 - Contributors: 40 - Last commit: Aug 30, 2026 - Latest release: v3.3.1 (Aug 30, 2026) - Install (npm): `npm install @penrose/core`, 949 downloads per week - Topics: Diagrams & diagrams as code ### Overview Penrose is an open-source diagram-as-code tool released under the MIT license. Its GitHub repository has 7,985 stars, 365 forks, and 40 contributors. It is actively developed with 48 commits in the last 12 months. The latest release, v3.3.1, was published on Aug 30, 2026. On npm it is downloaded about 949 times per week. ### Alternatives - [Mermaid](https://awesomedataviz.com/tools/mermaid/): Generate diagrams and flowcharts from markdown-like text definitions, with a live editor. (90.5K stars) - [Diagrams](https://awesomedataviz.com/tools/diagrams/): Diagram as code in Python for prototyping cloud system architectures. (42.7K stars) - [D2](https://awesomedataviz.com/tools/d2/): Declarative diagram scripting language that turns text into diagrams. (25.6K stars) - [PlantUML](https://awesomedataviz.com/tools/plantuml/): Generates UML, Gantt, mind map and other diagrams from plain text. (13.4K stars) - [Markmap](https://awesomedataviz.com/tools/markmap/): Builds interactive mind maps from Markdown. (13.1K stars) - [flowchart.js](https://awesomedataviz.com/tools/flowchart-js/): Draws SVG flowcharts from a textual description. (8.7K stars) Source: https://awesomedataviz.com/tools/penrose/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## go-echarts > Simple yet powerful data visualizing library for Go. - Category: [Go charting & plotting libraries](https://awesomedataviz.com/categories/go/) - Website: https://go-echarts.github.io/go-echarts/ - Repository: https://github.com/go-echarts/go-echarts - License: MIT - Language: Go - Status: Active (commits in the last 90 days) - GitHub stars: 7,645 - Commits in the last 12 months: 16 - Contributors: 63 - Last commit: Sep 13, 2026 - Latest release: v2.7.3 (Sep 27, 2026) - Install (Go): `go get github.com/go-echarts/go-echarts/v2` ### Overview go-echarts is an open-source Go plotting library released under the MIT license. Its GitHub repository has 7,645 stars, 593 forks, and 63 contributors. It is actively developed with 16 commits in the last 12 months. The latest release, v2.7.3, was published on Sep 27, 2026. ### Alternatives - [termui](https://awesomedataviz.com/tools/termui/): Terminal dashboard and widget library with charts, gauges, sparklines and more. (13.6K stars) - [go-diagrams](https://awesomedataviz.com/tools/go-diagrams/): Diagram-as-code library for system architecture diagrams in Go, rendered with Graphviz. (5.2K stars) - [asciigraph](https://awesomedataviz.com/tools/asciigraph/): Lightweight ASCII line graphs for command-line apps. (3.1K stars) - [termdash](https://awesomedataviz.com/tools/termdash/): Terminal-based dashboard library with line charts, bar charts, gauges and donuts. (3K stars) - [plot](https://awesomedataviz.com/tools/plot/): API for building and drawing plots in Go. (3K stars) - [svgo](https://awesomedataviz.com/tools/svgo/): Go Language Library for SVG generation. (2.3K stars) ### Comparisons - [go-echarts vs termui](https://awesomedataviz.com/compare/go-echarts-vs-termui/) - [go-diagrams vs go-echarts](https://awesomedataviz.com/compare/go-diagrams-vs-go-echarts/) - [asciigraph vs go-echarts](https://awesomedataviz.com/compare/asciigraph-vs-go-echarts/) - [go-echarts vs termdash](https://awesomedataviz.com/compare/go-echarts-vs-termdash/) Source: https://awesomedataviz.com/tools/go-echarts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## fl_chart > Customizable Flutter chart library with line, bar, pie, scatter and radar charts. - Category: [Flutter chart libraries](https://awesomedataviz.com/categories/flutter/) - Website: https://flchart.dev - Repository: https://github.com/imaNNeo/fl_chart - License: MIT - Language: Dart - Status: Active (commits in the last 90 days) - GitHub stars: 7,583 - Commits in the last 12 months: 51 - Contributors: 123 - Last commit: Sep 29, 2026 - Latest release: 1.2.0 (Mar 13, 2026) - Install (pub.dev): `flutter pub add fl_chart`, 1.9M downloads per 30 days ### Overview fl_chart is an open-source Flutter chart library released under the MIT license. Its GitHub repository has 7,583 stars, 1,969 forks, and 123 contributors. It is actively developed with 51 commits in the last 12 months. The latest release, 1.2.0, was published on Mar 13, 2026. On pub.dev it is downloaded about 1.9M times per 30 days. ### Alternatives - [MPAndroidChart](https://awesomedataviz.com/tools/mpandroidchart/): A powerful & easy to use chart library. (38.2K stars) - [Charts](https://awesomedataviz.com/tools/charts/): IOS port of MPAndroidChart. You can create charts for both platforms with very similar code. (28K stars) - [react-native-maps](https://awesomedataviz.com/tools/react-native-maps/): Map view component for iOS and Android in React Native. (16K stars) - [PNChart](https://awesomedataviz.com/tools/pnchart/): A simple and beautiful chart lib used in Piner and CoinsMan. (9.6K stars) - [F2](https://awesomedataviz.com/tools/f2/): An elegant, interactive and flexible charting library for mobile, maintained by Alibaba (8K stars) - [HelloCharts](https://awesomedataviz.com/tools/hellocharts/): Android chart library with line, column, pie, bubble and combo charts, plus zoom and scroll. (7.6K stars) ### Comparisons - [fl_chart vs flutter_map](https://awesomedataviz.com/compare/fl-chart-vs-flutter-map/) - [fl_chart vs Graphic](https://awesomedataviz.com/compare/fl-chart-vs-graphic/) Source: https://awesomedataviz.com/tools/fl-chart/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## HelloCharts > Android chart library with line, column, pie, bubble and combo charts, plus zoom and scroll. - Category: [Android chart libraries](https://awesomedataviz.com/categories/android/) - Repository: https://github.com/lecho/hellocharts-android - License: Apache-2.0 - Language: Java - Status: Inactive (no commits in over a year) - GitHub stars: 7,559 - Commits in the last 12 months: 0 - Contributors: 13 - Last commit: Mar 18, 2018 - Latest release: v1.5.8 (Sep 27, 2015) ### Overview HelloCharts is an open-source Android chart library released under the Apache-2.0 license. Its GitHub repository has 7,559 stars, 1,590 forks, and 13 contributors. It has not had a commit since Mar 18, 2018. The latest release, v1.5.8, was published on Sep 27, 2015. ### Alternatives - [MPAndroidChart](https://awesomedataviz.com/tools/mpandroidchart/): A powerful & easy to use chart library. (38.2K stars) - [WilliamChart](https://awesomedataviz.com/tools/williamchart/): Simple chart library. (5.1K stars) - [Vico](https://awesomedataviz.com/tools/vico/): Extensible chart library for Jetpack Compose and Compose Multiplatform. (3.2K stars) - [DecoView](https://awesomedataviz.com/tools/decoview/): Animated circular wheel chart library. (984 stars) ### Comparisons - [HelloCharts vs MPAndroidChart](https://awesomedataviz.com/compare/hellocharts-vs-mpandroidchart/) - [HelloCharts vs WilliamChart](https://awesomedataviz.com/compare/hellocharts-vs-williamchart/) - [HelloCharts vs Vico](https://awesomedataviz.com/compare/hellocharts-vs-vico/) - [DecoView vs HelloCharts](https://awesomedataviz.com/compare/decoview-vs-hellocharts/) Source: https://awesomedataviz.com/tools/hellocharts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## dc.js > Multi-dimensional charting built to work natively with crossfilter. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Repository: https://github.com/dc-js/dc.js - License: Apache-2.0 - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 7,430 - Commits in the last 12 months: 0 - Contributors: 111 - Last commit: Dec 1, 2023 - Latest release: 4.0.0 (Jan 29, 2020) - Install (npm): `npm install dc`, 23.4K downloads per week ### Overview dc.js is an open-source JavaScript charting library released under the Apache-2.0 license. Its GitHub repository has 7,430 stars, 1,756 forks, and 111 contributors. It has not had a commit since Dec 1, 2023. The latest release, 4.0.0, was published on Jan 29, 2020. On npm it is downloaded about 23.4K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/dc-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## folium > Builds interactive Leaflet.js maps from Python data. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://python-visualization.github.io/folium/ - Repository: https://github.com/python-visualization/folium - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 7,409 - Commits in the last 12 months: 161 - Contributors: 183 - Last commit: Oct 3, 2026 - Latest release: v0.20.0 (Jun 16, 2025) - Install (PyPI): `pip install folium`, 537.3K downloads per week - Topics: Maps & geospatial visualization ### Overview folium is an open-source Python visualization library released under the MIT license. Its GitHub repository has 7,409 stars, 2,263 forks, and 183 contributors. It is actively developed with 161 commits in the last 12 months. The latest release, v0.20.0, was published on Jun 16, 2025. On PyPI it is downloaded about 537.3K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/folium/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## MetricsGraphics.js > Optimized for time-series data. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://metricsgraphicsjs.org/ - Repository: https://github.com/metricsgraphics/metrics-graphics - License: MPL-2.0 - Language: TypeScript - Status: Inactive (no commits in over a year) - GitHub stars: 7,394 - Commits in the last 12 months: 0 - Contributors: 54 - Last commit: May 31, 2022 - Latest release: v2.11.0 (Dec 10, 2016) - Install (npm): `npm install metrics-graphics`, 6.5K downloads per week - Topics: Time series & real-time charts ### Overview MetricsGraphics.js is an open-source JavaScript charting library released under the MPL-2.0 license. Its GitHub repository has 7,394 stars, 460 forks, and 54 contributors. It has not had a commit since May 31, 2022. The latest release, v2.11.0, was published on Dec 10, 2016. On npm it is downloaded about 6.5K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/metricsgraphics-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## NVD3 > A reusable charting library written in d3.js. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: http://nvd3.org/ - Repository: https://github.com/novus/nvd3 - License: Apache-2.0 - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 7,229 - Commits in the last 12 months: 0 - Contributors: 196 - Last commit: Jun 30, 2018 - Latest release: v1.8.6 (Aug 24, 2017) - Install (npm): `npm install nvd3`, 100.9K downloads per week ### Overview NVD3 is an open-source JavaScript charting library released under the Apache-2.0 license. Its GitHub repository has 7,229 stars, 2,064 forks, and 196 contributors. It has not had a commit since Jun 30, 2018. The latest release, v1.8.6, was published on Aug 24, 2017. On npm it is downloaded about 100.9K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/nvd3/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## TensorBoard > TensorFlow's visualization toolkit for metrics, model graphs, embeddings and more. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Repository: https://github.com/tensorflow/tensorboard - License: Apache-2.0 - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 7,229 - Commits in the last 12 months: 40 - Contributors: 292 - Last commit: Aug 24, 2026 - Latest release: 2.21.0 (Jun 29, 2026) - Topics: Machine learning & AI visualization ### Overview TensorBoard is an open-source ML visualization tool released under the Apache-2.0 license. Its GitHub repository has 7,229 stars, 1,715 forks, and 292 contributors. It is actively developed with 40 commits in the last 12 months. The latest release, 2.21.0, was published on Jun 29, 2026. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) Source: https://awesomedataviz.com/tools/tensorboard/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## roughViz > Sketchy, hand-drawn style charts for the browser, based on Rough.js. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://www.jwilber.me/roughviz/ - Repository: https://github.com/jwilber/roughViz - License: MIT - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 7,161 - Commits in the last 12 months: 0 - Contributors: 11 - Last commit: Nov 23, 2023 - Install (npm): `npm install rough-viz`, 1.5K downloads per week ### Overview roughViz is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 7,161 stars, 241 forks, and 11 contributors. It has not had a commit since Nov 23, 2023. On npm it is downloaded about 1.5K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/roughviz/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## SandDance > Visual data exploration and presentation with animated unit visualizations, from Microsoft Research. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://microsoft.github.io/SandDance - Repository: https://github.com/microsoft/SandDance - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 7,147 - Commits in the last 12 months: 67 - Contributors: 23 - Last commit: Sep 28, 2026 - Latest release: v3 (Aug 3, 2022) - Topics: Exploratory data analysis tools ### Overview SandDance is an open-source data visualization app released under the MIT license. Its GitHub repository has 7,147 stars, 574 forks, and 23 contributors. It is actively developed with 67 commits in the last 12 months. The latest release, v3, was published on Aug 3, 2022. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/sanddance/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ggplot2 > A plotting system based on the grammar of graphics. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://ggplot2.tidyverse.org/ - Repository: https://github.com/tidyverse/ggplot2 - License: MIT - Language: R - Status: Active (commits in the last 90 days) - GitHub stars: 7,005 - Commits in the last 12 months: 86 - Contributors: 354 - Last commit: Oct 2, 2026 - Latest release: v4.0.3 (Apr 22, 2026) - Install (CRAN): `install.packages("ggplot2")`, 471.1K downloads per week - Topics: Grammar of graphics libraries ### Overview ggplot2 is an open-source R visualization package released under the MIT license. Its GitHub repository has 7,005 stars, 2,125 forks, and 354 contributors. It is actively developed with 86 commits in the last 12 months. The latest release, v4.0.3, was published on Apr 22, 2026. On CRAN it is downloaded about 471.1K times per week. ### Alternatives - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) - [gt](https://awesomedataviz.com/tools/gt/): Builds publication-quality display tables in R. (2.2K stars) ### Comparisons - [ggplot2 vs Shiny](https://awesomedataviz.com/compare/ggplot2-vs-shiny/) - [ggplot2 vs plotly (R)](https://awesomedataviz.com/compare/ggplot2-vs-plotly-r/) - [ggplot2 vs patchwork](https://awesomedataviz.com/compare/ggplot2-vs-patchwork/) - [ggplot2 vs ggstatsplot](https://awesomedataviz.com/compare/ggplot2-vs-ggstatsplot/) - [ggplot2 vs Matplotlib](https://awesomedataviz.com/compare/ggplot2-vs-matplotlib/) - [ggplot2 vs plotnine](https://awesomedataviz.com/compare/ggplot2-vs-plotnine/) Source: https://awesomedataviz.com/tools/ggplot2/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Evidence > Business intelligence as code: build reports and dashboards with SQL and Markdown. - Category: [Open-source dashboards & BI tools](https://awesomedataviz.com/categories/dashboards-and-bi/) - Website: https://evidence.dev - Repository: https://github.com/evidence-dev/evidence - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 6,978 - Commits in the last 12 months: 204 - Contributors: 67 - Last commit: Oct 2, 2026 - Latest release: @evidence-dev/evidence@40.1.8 (Feb 6, 2026) - Topics: Dashboards & BI ### Overview Evidence is an open-source dashboard and BI tool released under the MIT license. Its GitHub repository has 6,978 stars, 425 forks, and 67 contributors. It is actively developed with 204 commits in the last 12 months. The latest release, @evidence-dev/evidence@40.1.8, was published on Feb 6, 2026. ### Alternatives - [Grafana](https://awesomedataviz.com/tools/grafana/): Observability and data visualization platform for metrics, logs and traces from many data sources. (77.1K stars) - [Apache Superset](https://awesomedataviz.com/tools/superset/): Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. (75K stars) - [Metabase](https://awesomedataviz.com/tools/metabase/): Business intelligence tool for querying data and building dashboards, with embedded analytics. (49.5K stars) - [Redash](https://awesomedataviz.com/tools/redash/): Query data sources with SQL, then visualize the results and build dashboards. (28.8K stars) - [Kibana](https://awesomedataviz.com/tools/kibana/): Visualization and dashboard UI for data stored in Elasticsearch. (21.3K stars) - [Lightdash](https://awesomedataviz.com/tools/lightdash/): BI tool that turns dbt projects into metrics, charts and dashboards. (6.2K stars) Source: https://awesomedataviz.com/tools/evidence/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## react-chartjs-2 > React components for Chart.js. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://react-chartjs-2.js.org - Repository: https://github.com/reactchartjs/react-chartjs-2 - License: MIT - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 6,939 - Commits in the last 12 months: 44 - Contributors: 69 - Last commit: May 26, 2026 - Latest release: v5.3.1 (Oct 27, 2025) - Install (npm): `npm install react-chartjs-2`, 5.7M downloads per week ### Overview react-chartjs-2 is an open-source React chart library released under the MIT license. Its GitHub repository has 6,939 stars, 2,432 forks, and 69 contributors. It is maintained with 44 commits in the last 12 months; the most recent commit was on May 26, 2026. The latest release, v5.3.1, was published on Oct 27, 2025. On npm it is downloaded about 5.7M times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) Source: https://awesomedataviz.com/tools/react-chartjs-2/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Vue Flow > Flowchart and node-based graph component for Vue 3. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Website: https://vueflow.dev - Repository: https://github.com/bcakmakoglu/vue-flow - License: MIT - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 6,888 - Commits in the last 12 months: 22 - Contributors: 29 - Last commit: Jun 23, 2026 - Latest release: v1.48.2 (Jan 28, 2026) - Install (npm): `npm install @vue-flow/core`, 705.2K downloads per week - Topics: Graph & network visualization, Diagrams & diagrams as code ### Overview Vue Flow is an open-source JavaScript graph visualization library released under the MIT license. Its GitHub repository has 6,888 stars, 413 forks, and 29 contributors. It is maintained with 22 commits in the last 12 months; the most recent commit was on Jun 23, 2026. The latest release, v1.48.2, was published on Jan 28, 2026. On npm it is downloaded about 705.2K times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) - [3d-force-graph](https://awesomedataviz.com/tools/3d-force-graph/): 3D force-directed graph component using Three.js/WebGL. (6.4K stars) ### Comparisons - [Vue Flow vs xyflow](https://awesomedataviz.com/compare/vue-flow-vs-xyflow/) - [G6 vs Vue Flow](https://awesomedataviz.com/compare/g6-vs-vue-flow/) - [Sigma.js vs Vue Flow](https://awesomedataviz.com/compare/sigma-js-vs-vue-flow/) - [Cytoscape.js vs Vue Flow](https://awesomedataviz.com/compare/cytoscape-js-vs-vue-flow/) Source: https://awesomedataviz.com/tools/vue-flow/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ScottPlot > Interactive plotting library for .NET with WinForms, WPF, Avalonia, Blazor and other controls. - Category: [C# & .NET charting libraries](https://awesomedataviz.com/categories/dotnet/) - Website: https://ScottPlot.net - Repository: https://github.com/ScottPlot/ScottPlot - License: MIT - Language: C# - Status: Active (commits in the last 90 days) - GitHub stars: 6,766 - Commits in the last 12 months: 126 - Contributors: 190 - Last commit: Aug 15, 2026 - Latest release: 5.1.59 (Jun 22, 2026) - Install (NuGet): `dotnet add package ScottPlot`, 6.1M downloads in total ### Overview ScottPlot is an open-source .NET charting library released under the MIT license. Its GitHub repository has 6,766 stars, 1,015 forks, and 190 contributors. It is actively developed with 126 commits in the last 12 months. The latest release, 5.1.59, was published on Jun 22, 2026. It has been downloaded about 6.1M times from NuGet. ### Alternatives - [LiveCharts2](https://awesomedataviz.com/tools/livecharts2/): Animated, interactive charts, maps and gauges for .NET UI frameworks. (5.5K stars) - [OxyPlot](https://awesomedataviz.com/tools/oxyplot/): Cross-platform plotting library for .NET. (3.5K stars) - [Microcharts](https://awesomedataviz.com/tools/microcharts/): Simple cross-platform charts for .NET, drawn with SkiaSharp. (2.1K stars) - [Mapsui](https://awesomedataviz.com/tools/mapsui/): .NET map component for MAUI, Avalonia, Uno Platform, Blazor, WPF and WinUI. (1.6K stars) - [MSAGL](https://awesomedataviz.com/tools/msagl/): Microsoft Automatic Graph Layout: tools for graph layout and viewing in .NET. (1.5K stars) ### Comparisons - [LiveCharts2 vs ScottPlot](https://awesomedataviz.com/compare/livecharts2-vs-scottplot/) - [OxyPlot vs ScottPlot](https://awesomedataviz.com/compare/oxyplot-vs-scottplot/) - [Microcharts vs ScottPlot](https://awesomedataviz.com/compare/microcharts-vs-scottplot/) - [Mapsui vs ScottPlot](https://awesomedataviz.com/compare/mapsui-vs-scottplot/) Source: https://awesomedataviz.com/tools/scottplot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## X6 > Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Website: https://x6.antv.antgroup.com - Repository: https://github.com/antvis/X6 - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 6,716 - Commits in the last 12 months: 116 - Contributors: 129 - Last commit: Aug 11, 2026 - Latest release: v3.1.7 (Mar 18, 2026) - Install (npm): `npm install @antv/x6`, 198.5K downloads per week - Topics: Graph & network visualization, Diagrams & diagrams as code ### Overview X6 is an open-source JavaScript graph visualization library released under the MIT license. Its GitHub repository has 6,716 stars, 1,893 forks, and 129 contributors. It is actively developed with 116 commits in the last 12 months. The latest release, v3.1.7, was published on Mar 18, 2026. On npm it is downloaded about 198.5K times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [3d-force-graph](https://awesomedataviz.com/tools/3d-force-graph/): 3D force-directed graph component using Three.js/WebGL. (6.4K stars) Source: https://awesomedataviz.com/tools/x6/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Gephi > An open-source platform for visualizing and manipulating large graphs - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: http://gephi.org - Repository: https://github.com/gephi/gephi - License: GPL-3.0 - Language: Java - Status: Active (commits in the last 90 days) - GitHub stars: 6,658 - Commits in the last 12 months: 1,506 - Contributors: 114 - Last commit: Oct 2, 2026 - Latest release: v0.11.3 (Sep 6, 2026) - Topics: Graph & network visualization, GPU-accelerated & WebGL visualization ### Overview Gephi is an open-source data visualization app released under the GPL-3.0 license. Its GitHub repository has 6,658 stars, 1,611 forks, and 114 contributors. It is actively developed with 1,506 commits in the last 12 months. The latest release, v0.11.3, was published on Sep 6, 2026. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/gephi/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Charts.css > CSS framework that styles HTML tables as charts. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://ChartsCSS.org - Repository: https://github.com/ChartsCSS/charts.css - License: MIT - Language: HTML - Status: Inactive (no commits in over a year) - GitHub stars: 6,582 - Commits in the last 12 months: 0 - Contributors: 2 - Last commit: Jul 21, 2025 - Latest release: 1.2.0 (Jul 21, 2025) - Install (npm): `npm install charts.css`, 19.9K downloads per week ### Overview Charts.css is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 6,582 stars, 179 forks, and 2 contributors. It has not had a commit since Jul 21, 2025. The latest release, 1.2.0, was published on Jul 21, 2025. On npm it is downloaded about 19.9K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/charts-css/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Chartkick > Create charts with one line of Ruby. - Category: [Ruby charting libraries](https://awesomedataviz.com/categories/ruby/) - Website: https://chartkick.com - Repository: https://github.com/ankane/chartkick - License: MIT - Language: Ruby - Status: Active (commits in the last 90 days) - GitHub stars: 6,528 - Commits in the last 12 months: 10 - Contributors: 24 - Last commit: Aug 15, 2026 - Install (RubyGems): `gem install chartkick` ### Overview Chartkick is an open-source Ruby charting library released under the MIT license. Its GitHub repository has 6,528 stars, 561 forks, and 24 contributors. It is actively developed with 10 commits in the last 12 months. ### Alternatives - [YouPlot](https://awesomedataviz.com/tools/youplot/): Command-line tool that draws plots in the terminal from piped data. (4.9K stars) - [Blazer](https://awesomedataviz.com/tools/blazer/): Business intelligence tool for Rails apps: explore data with SQL and build charts and dashboards. (4.8K stars) - [Gruff](https://awesomedataviz.com/tools/gruff/): Graphing library for Ruby that renders charts as images using RMagick. (1.4K stars) ### Comparisons - [Chartkick vs YouPlot](https://awesomedataviz.com/compare/chartkick-vs-youplot/) - [Blazer vs Chartkick](https://awesomedataviz.com/compare/blazer-vs-chartkick/) - [Chartkick vs Gruff](https://awesomedataviz.com/compare/chartkick-vs-gruff/) Source: https://awesomedataviz.com/tools/chartkick/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## 3d-force-graph > 3D force-directed graph component using Three.js/WebGL. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Website: https://vasturiano.github.io/3d-force-graph/example/large-graph/ - Repository: https://github.com/vasturiano/3d-force-graph - License: MIT - Language: HTML - Status: Active (commits in the last 90 days) - GitHub stars: 6,433 - Commits in the last 12 months: 9 - Contributors: 15 - Last commit: Sep 29, 2026 - Install (npm): `npm install 3d-force-graph`, 488.8K downloads per week - Topics: Graph & network visualization, 3D & scientific visualization, GPU-accelerated & WebGL visualization ### Overview 3d-force-graph is an open-source JavaScript graph visualization library released under the MIT license. Its GitHub repository has 6,433 stars, 1,021 forks, and 15 contributors. It is actively developed with 9 commits in the last 12 months. On npm it is downloaded about 488.8K times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) Source: https://awesomedataviz.com/tools/3d-force-graph/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Aim > Experiment tracker with a UI to explore and compare ML runs and metrics. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Website: https://aimstack.io - Repository: https://github.com/aimhubio/aim - License: Apache-2.0 - Language: Python - Status: Maintained (commits in the last 12 months) - GitHub stars: 6,276 - Commits in the last 12 months: 1 - Contributors: 82 - Last commit: Dec 31, 2025 - Latest release: v3.29.1 (May 8, 2025) - Topics: Machine learning & AI visualization ### Overview Aim is an open-source ML visualization tool released under the Apache-2.0 license. Its GitHub repository has 6,276 stars, 413 forks, and 82 contributors. It is maintained with 1 commit in the last 12 months; the most recent commit was on Dec 31, 2025. The latest release, v3.29.1, was published on May 8, 2025. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) Source: https://awesomedataviz.com/tools/aim/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ImPlot > Immediate-mode plotting library for Dear ImGui. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Repository: https://github.com/epezent/implot - License: MIT - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 6,239 - Commits in the last 12 months: 104 - Contributors: 55 - Last commit: Sep 24, 2026 - Latest release: v1.0 (Apr 5, 2026) ### Overview ImPlot is an open-source C++ visualization tool released under the MIT license. Its GitHub repository has 6,239 stars, 695 forks, and 55 contributors. It is actively developed with 104 commits in the last 12 months. The latest release, v1.0, was published on Apr 5, 2026. ### Alternatives - [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/): Open-source Qt5 application to plot charts (based on Qwt). (6.2K stars) - [Matplot++](https://awesomedataviz.com/tools/matplotpp/): C++ graphics library for data visualization with a MATLAB-like API. (4.9K stars) - [F3D](https://awesomedataviz.com/tools/f3d/): Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. (4.7K stars) - [Mapnik](https://awesomedataviz.com/tools/mapnik/): Toolkit for rendering maps, widely used to render OpenStreetMap tiles. (4K stars) - [ROOT](https://awesomedataviz.com/tools/root/): CERN framework for analyzing, storing and visualizing large scientific datasets. (3.3K stars) - [VTK](https://awesomedataviz.com/tools/vtk/): Open-source library for 3d Graphics, image processing and visualization. (3.2K stars) ### Comparisons - [ImPlot vs PlotJuggler](https://awesomedataviz.com/compare/implot-vs-plotjuggler/) - [ImPlot vs Matplot++](https://awesomedataviz.com/compare/implot-vs-matplotpp/) - [F3D vs ImPlot](https://awesomedataviz.com/compare/f3d-vs-implot/) - [ImPlot vs Mapnik](https://awesomedataviz.com/compare/implot-vs-mapnik/) Source: https://awesomedataviz.com/tools/implot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## PlotJuggler > Open-source Qt5 application to plot charts (based on Qwt). - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Website: https://www.plotjuggler.io - Repository: https://github.com/PlotJuggler/PlotJuggler - License: MPL-2.0 - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 6,230 - Commits in the last 12 months: 615 - Contributors: 5 - Last commit: Oct 1, 2026 - Latest release: 4.0.0 (Sep 21, 2026) - Topics: Time series & real-time charts ### Overview PlotJuggler is an open-source C++ visualization tool released under the MPL-2.0 license. Its GitHub repository has 6,230 stars, 826 forks, and 5 contributors. It is actively developed with 615 commits in the last 12 months. The latest release, 4.0.0, was published on Sep 21, 2026. ### Alternatives - [ImPlot](https://awesomedataviz.com/tools/implot/): Immediate-mode plotting library for Dear ImGui. (6.2K stars) - [Matplot++](https://awesomedataviz.com/tools/matplotpp/): C++ graphics library for data visualization with a MATLAB-like API. (4.9K stars) - [F3D](https://awesomedataviz.com/tools/f3d/): Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. (4.7K stars) - [Mapnik](https://awesomedataviz.com/tools/mapnik/): Toolkit for rendering maps, widely used to render OpenStreetMap tiles. (4K stars) - [ROOT](https://awesomedataviz.com/tools/root/): CERN framework for analyzing, storing and visualizing large scientific datasets. (3.3K stars) - [VTK](https://awesomedataviz.com/tools/vtk/): Open-source library for 3d Graphics, image processing and visualization. (3.2K stars) ### Comparisons - [ImPlot vs PlotJuggler](https://awesomedataviz.com/compare/implot-vs-plotjuggler/) - [Matplot++ vs PlotJuggler](https://awesomedataviz.com/compare/matplotpp-vs-plotjuggler/) - [F3D vs PlotJuggler](https://awesomedataviz.com/compare/f3d-vs-plotjuggler/) - [Mapnik vs PlotJuggler](https://awesomedataviz.com/compare/mapnik-vs-plotjuggler/) Source: https://awesomedataviz.com/tools/plotjuggler/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## BizCharts > Data visualization library based on G2 and React. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: http://bizcharts.net/products/bizCharts - Repository: https://github.com/alibaba/BizCharts - License: MIT - Language: TypeScript - Status: Inactive (no commits in over a year) - GitHub stars: 6,189 - Commits in the last 12 months: 0 - Contributors: 62 - Last commit: May 23, 2025 - Latest release: v4.1.15 (Dec 7, 2021) - Install (npm): `npm install bizcharts`, 26.4K downloads per week - Topics: Grammar of graphics libraries ### Overview BizCharts is an open-source React chart library released under the MIT license. Its GitHub repository has 6,189 stars, 656 forks, and 62 contributors. It has not had a commit since May 23, 2025. The latest release, v4.1.15, was published on Dec 7, 2021. On npm it is downloaded about 26.4K times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) Source: https://awesomedataviz.com/tools/bizcharts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Lightdash > BI tool that turns dbt projects into metrics, charts and dashboards. - Category: [Open-source dashboards & BI tools](https://awesomedataviz.com/categories/dashboards-and-bi/) - Website: https://lightdash.com - Repository: https://github.com/lightdash/lightdash - License: Other - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 6,174 - Commits in the last 12 months: 12,219 - Contributors: 170 - Last commit: Oct 4, 2026 - Latest release: 2.425.0 (Oct 4, 2026) - Topics: Dashboards & BI ### Overview Lightdash is a dashboard and BI tool. Its GitHub repository has 6,174 stars, 790 forks, and 170 contributors. It is actively developed with 12,219 commits in the last 12 months. The latest release, 2.425.0, was published on Oct 4, 2026. ### Alternatives - [Grafana](https://awesomedataviz.com/tools/grafana/): Observability and data visualization platform for metrics, logs and traces from many data sources. (77.1K stars) - [Apache Superset](https://awesomedataviz.com/tools/superset/): Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. (75K stars) - [Metabase](https://awesomedataviz.com/tools/metabase/): Business intelligence tool for querying data and building dashboards, with embedded analytics. (49.5K stars) - [Redash](https://awesomedataviz.com/tools/redash/): Query data sources with SQL, then visualize the results and build dashboards. (28.8K stars) - [Kibana](https://awesomedataviz.com/tools/kibana/): Visualization and dashboard UI for data stored in Elasticsearch. (21.3K stars) - [Evidence](https://awesomedataviz.com/tools/evidence/): Business intelligence as code: build reports and dashboards with SQL and Markdown. (7K stars) Source: https://awesomedataviz.com/tools/lightdash/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Frappe Gantt > Simple, interactive SVG Gantt chart library. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://frappe.io/gantt - Repository: https://github.com/frappe/gantt - License: MIT - Language: JavaScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 6,134 - Commits in the last 12 months: 38 - Contributors: 40 - Last commit: Mar 5, 2026 - Latest release: v1.0.3 (Feb 3, 2025) - Install (npm): `npm install frappe-gantt`, 268.1K downloads per week ### Overview Frappe Gantt is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 6,134 stars, 1,279 forks, and 40 contributors. It is maintained with 38 commits in the last 12 months; the most recent commit was on Mar 5, 2026. The latest release, v1.0.3, was published on Feb 3, 2025. On npm it is downloaded about 268.1K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/frappe-gantt/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Textures.js > A library to create SVG patterns. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://riccardoscalco.github.io/textures/ - Repository: https://github.com/riccardoscalco/textures - License: MIT - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 6,088 - Commits in the last 12 months: 0 - Contributors: 10 - Last commit: Jan 24, 2022 - Latest release: v1.2.3 (Apr 17, 2021) - Install (npm): `npm install textures`, 4.7K downloads per week ### Overview Textures.js is an open-source JavaScript visualization library released under the MIT license. Its GitHub repository has 6,088 stars, 219 forks, and 10 contributors. It has not had a commit since Jan 24, 2022. The latest release, v1.2.3, was published on Apr 17, 2021. On npm it is downloaded about 4.7K times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) - [Vega-Lite](https://awesomedataviz.com/tools/vega-lite/): Is a high-level grammar of interactive graphics. It provides a concise JSON syntax for rapidly generating visualizations to support analysis. (5.5K stars) ### Comparisons - [blessed-contrib vs Textures.js](https://awesomedataviz.com/compare/blessed-contrib-vs-textures-js/) - [Textures.js vs Vega](https://awesomedataviz.com/compare/textures-js-vs-vega/) - [Perspective vs Textures.js](https://awesomedataviz.com/compare/perspective-vs-textures-js/) - [Textures.js vs vue-echarts](https://awesomedataviz.com/compare/textures-js-vs-vue-echarts/) Source: https://awesomedataviz.com/tools/textures-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Spark > Sparklines for the shell. It has several implementations in different languages. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: http://zachholman.com/spark/ - Repository: https://github.com/holman/spark - License: MIT - Language: Shell - Status: Inactive (no commits in over a year) - GitHub stars: 6,068 - Commits in the last 12 months: 0 - Contributors: 22 - Last commit: Mar 14, 2017 - Topics: Terminal & command-line charts ### Overview Spark is an open-source data visualization app released under the MIT license. Its GitHub repository has 6,068 stars, 287 forks, and 22 contributors. It has not had a commit since Mar 14, 2017. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/spark/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## billboard.js > Reusable D3.js-based chart library with SVG and Canvas rendering, maintained by NAVER. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://naver.github.io/billboard.js/ - Repository: https://github.com/naver/billboard.js - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 6,014 - Commits in the last 12 months: 138 - Contributors: 150 - Last commit: Sep 30, 2026 - Latest release: 4.1.1 (Sep 30, 2026) - Install (npm): `npm install billboard.js`, 46.8K downloads per week ### Overview billboard.js is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 6,014 stars, 359 forks, and 150 contributors. It is actively developed with 138 commits in the last 12 months. The latest release, 4.1.1, was published on Sep 30, 2026. On npm it is downloaded about 46.8K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/billboard-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Voilà > Turns Jupyter notebooks into standalone interactive web applications. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://voila.readthedocs.io - Repository: https://github.com/voila-dashboards/voila - License: BSD - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 5,947 - Commits in the last 12 months: 12 - Contributors: 73 - Last commit: Sep 4, 2026 - Latest release: v0.5.13 (Sep 4, 2026) - Install (PyPI): `pip install voila`, 28.1K downloads per week - Topics: Jupyter & notebook visualization ### Overview Voilà is an open-source Python visualization library released under the BSD license. Its GitHub repository has 5,947 stars, 528 forks, and 73 contributors. It is actively developed with 12 commits in the last 12 months. The latest release, v0.5.13, was published on Sep 4, 2026. On PyPI it is downloaded about 28.1K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/voila/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## MUI X Charts > React chart components from MUI; the community package is MIT-licensed. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://mui.com/x/ - Repository: https://github.com/mui/mui-x - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 5,859 - Commits in the last 12 months: 2,335 - Contributors: 473 - Last commit: Oct 3, 2026 - Latest release: v9.14.0 (Sep 17, 2026) - Install (npm): `npm install @mui/x-charts`, 1.3M downloads per week ### Overview MUI X Charts is an open-source React chart library released under the MIT license. Its GitHub repository has 5,859 stars, 1,829 forks, and 473 contributors. It is actively developed with 2,335 commits in the last 12 months. The latest release, v9.14.0, was published on Sep 17, 2026. On npm it is downloaded about 1.3M times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) Source: https://awesomedataviz.com/tools/mui-x-charts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## dagre > Directed graph layout library for JavaScript. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Repository: https://github.com/dagrejs/dagre - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 5,814 - Commits in the last 12 months: 110 - Contributors: 39 - Last commit: Aug 8, 2026 - Latest release: v2.0.0 (Nov 23, 2025) - Install (npm): `npm install @dagrejs/dagre`, 5.8M downloads per week - Topics: Graph & network visualization ### Overview dagre is an open-source JavaScript graph visualization library released under the MIT license. Its GitHub repository has 5,814 stars, 641 forks, and 39 contributors. It is actively developed with 110 commits in the last 12 months. The latest release, v2.0.0, was published on Nov 23, 2025. On npm it is downloaded about 5.8M times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) Source: https://awesomedataviz.com/tools/dagre/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## LikeC4 > Architecture-as-code language and tools that generate live, interactive diagrams. - Category: [Diagrams as code](https://awesomedataviz.com/categories/diagrams-as-code/) - Website: https://likec4.dev - Repository: https://github.com/likec4/likec4 - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 5,809 - Commits in the last 12 months: 1,831 - Contributors: 61 - Last commit: Sep 21, 2026 - Latest release: v1.59.4 (Sep 21, 2026) - Install (npm): `npm install likec4`, 133.6K downloads per week - Topics: Diagrams & diagrams as code ### Overview LikeC4 is an open-source diagram-as-code tool released under the MIT license. Its GitHub repository has 5,809 stars, 395 forks, and 61 contributors. It is actively developed with 1,831 commits in the last 12 months. The latest release, v1.59.4, was published on Sep 21, 2026. On npm it is downloaded about 133.6K times per week. ### Alternatives - [Mermaid](https://awesomedataviz.com/tools/mermaid/): Generate diagrams and flowcharts from markdown-like text definitions, with a live editor. (90.5K stars) - [Diagrams](https://awesomedataviz.com/tools/diagrams/): Diagram as code in Python for prototyping cloud system architectures. (42.7K stars) - [D2](https://awesomedataviz.com/tools/d2/): Declarative diagram scripting language that turns text into diagrams. (25.6K stars) - [PlantUML](https://awesomedataviz.com/tools/plantuml/): Generates UML, Gantt, mind map and other diagrams from plain text. (13.4K stars) - [Markmap](https://awesomedataviz.com/tools/markmap/): Builds interactive mind maps from Markdown. (13.1K stars) - [flowchart.js](https://awesomedataviz.com/tools/flowchart-js/): Draws SVG flowcharts from a textual description. (8.7K stars) Source: https://awesomedataviz.com/tools/likec4/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Panel > Data exploration and web app framework for Python that works with many plotting libraries. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://panel.holoviz.org - Repository: https://github.com/holoviz/panel - License: BSD-3-Clause - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 5,782 - Commits in the last 12 months: 392 - Contributors: 225 - Last commit: Oct 4, 2026 - Latest release: v1.9.4 (Aug 17, 2026) - Install (PyPI): `pip install panel`, 279.2K downloads per week - Topics: Dashboards & BI, Jupyter & notebook visualization, Exploratory data analysis tools ### Overview Panel is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 5,782 stars, 635 forks, and 225 contributors. It is actively developed with 392 commits in the last 12 months. The latest release, v1.9.4, was published on Aug 17, 2026. On PyPI it is downloaded about 279.2K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) ### Comparisons - [Panel vs Streamlit](https://awesomedataviz.com/compare/panel-vs-streamlit/) Source: https://awesomedataviz.com/tools/panel/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## vue-chartjs > Vue.js wrapper for Chart.js. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://vue-chartjs.org - Repository: https://github.com/apertureless/vue-chartjs - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 5,718 - Commits in the last 12 months: 5 - Contributors: 100 - Last commit: Jul 7, 2026 - Latest release: v5.3.4 (Jul 7, 2026) - Install (npm): `npm install vue-chartjs`, 1.2M downloads per week ### Overview vue-chartjs is an open-source JavaScript visualization library released under the MIT license. Its GitHub repository has 5,718 stars, 801 forks, and 100 contributors. It is actively developed with 5 commits in the last 12 months. The latest release, v5.3.4, was published on Jul 7, 2026. On npm it is downloaded about 1.2M times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [Vega-Lite](https://awesomedataviz.com/tools/vega-lite/): Is a high-level grammar of interactive graphics. It provides a concise JSON syntax for rapidly generating visualizations to support analysis. (5.5K stars) Source: https://awesomedataviz.com/tools/vue-chartjs/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Orange > Visual programming tool for data mining, machine learning and interactive data visualization. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://orangedatamining.com - Repository: https://github.com/biolab/orange3 - License: Other - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 5,717 - Commits in the last 12 months: 309 - Contributors: 108 - Last commit: Sep 28, 2026 - Latest release: 3.40.0 (Dec 20, 2025) - Topics: Machine learning & AI visualization ### Overview Orange is a data visualization app. Its GitHub repository has 5,717 stars, 1,114 forks, and 108 contributors. It is actively developed with 309 commits in the last 12 months. The latest release, 3.40.0, was published on Dec 20, 2025. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/orange/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Shiny > Framework for creating interactive applications/visualisations - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://shiny.rstudio.com - Repository: https://github.com/rstudio/shiny - License: MIT - Language: R - Status: Active (commits in the last 90 days) - GitHub stars: 5,694 - Commits in the last 12 months: 63 - Contributors: 92 - Last commit: Oct 2, 2026 - Latest release: v1.14.0 (Jun 22, 2026) - Install (CRAN): `install.packages("shiny")`, 192.4K downloads per week - Install (npm): `npm install @posit/shiny`, 13 downloads per week - Topics: Dashboards & BI ### Overview Shiny is an open-source R visualization package released under the MIT license. Its GitHub repository has 5,694 stars, 1,891 forks, and 92 contributors. It is actively developed with 63 commits in the last 12 months. The latest release, v1.14.0, was published on Jun 22, 2026. On CRAN it is downloaded about 192.4K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) - [gt](https://awesomedataviz.com/tools/gt/): Builds publication-quality display tables in R. (2.2K stars) ### Comparisons - [ggplot2 vs Shiny](https://awesomedataviz.com/compare/ggplot2-vs-shiny/) - [plotly (R) vs Shiny](https://awesomedataviz.com/compare/plotly-r-vs-shiny/) - [patchwork vs Shiny](https://awesomedataviz.com/compare/patchwork-vs-shiny/) - [ggstatsplot vs Shiny](https://awesomedataviz.com/compare/ggstatsplot-vs-shiny/) - [Shiny vs Streamlit](https://awesomedataviz.com/compare/shiny-vs-streamlit/) Source: https://awesomedataviz.com/tools/shiny/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ChartView > Line, bar and pie chart views built with SwiftUI. - Category: [iOS & Swift chart libraries](https://awesomedataviz.com/categories/ios/) - Repository: https://github.com/AppPear/ChartView - License: MIT - Language: Swift - Status: Maintained (commits in the last 12 months) - GitHub stars: 5,646 - Commits in the last 12 months: 15 - Contributors: 29 - Last commit: Mar 2, 2026 - Latest release: 2.0.0 (Mar 2, 2026) ### Overview ChartView is an open-source iOS chart library released under the MIT license. Its GitHub repository has 5,646 stars, 635 forks, and 29 contributors. It is maintained with 15 commits in the last 12 months; the most recent commit was on Mar 2, 2026. The latest release, 2.0.0, was published on Mar 2, 2026. ### Alternatives - [Charts](https://awesomedataviz.com/tools/charts/): IOS port of MPAndroidChart. You can create charts for both platforms with very similar code. (28K stars) - [PNChart](https://awesomedataviz.com/tools/pnchart/): A simple and beautiful chart lib used in Piner and CoinsMan. (9.6K stars) - [JBChartView](https://awesomedataviz.com/tools/jbchartview/): Charting library for both line and bar graphs. (3.7K stars) - [Core Plot](https://awesomedataviz.com/tools/core-plot/): 2D plotting framework for macOS, iOS and tvOS. (2.8K stars) - [BEMSimpleLineGraph](https://awesomedataviz.com/tools/bemsimplelinegraph/): Highly customizable and interactive line graphs. (2.6K stars) - [SwiftCharts](https://awesomedataviz.com/tools/swiftcharts/): Customizable charts library for iOS. (2.6K stars) ### Comparisons - [Charts vs ChartView](https://awesomedataviz.com/compare/charts-vs-chartview/) - [ChartView vs PNChart](https://awesomedataviz.com/compare/chartview-vs-pnchart/) - [ChartView vs JBChartView](https://awesomedataviz.com/compare/chartview-vs-jbchartview/) - [ChartView vs Core Plot](https://awesomedataviz.com/compare/chartview-vs-core-plot/) Source: https://awesomedataviz.com/tools/chartview/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Potree > WebGL point cloud viewer for large datasets such as LiDAR scans. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: http://potree.org - Repository: https://github.com/potree/potree - License: Other - Language: JavaScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 5,628 - Commits in the last 12 months: 1 - Contributors: 43 - Last commit: Jan 8, 2026 - Latest release: 1.8.2 (Dec 12, 2023) - Topics: 3D & scientific visualization, GPU-accelerated & WebGL visualization, Visualizing large datasets ### Overview Potree is a JavaScript mapping library. Its GitHub repository has 5,628 stars, 1,366 forks, and 43 contributors. It is maintained with 1 commit in the last 12 months; the most recent commit was on Jan 8, 2026. The latest release, 1.8.2, was published on Dec 12, 2023. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/potree/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Vega-Lite > Is a high-level grammar of interactive graphics. It provides a concise JSON syntax for rapidly generating visualizations to support analysis. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://vega.github.io/vega-lite/ - Repository: https://github.com/vega/vega-lite - License: BSD-3-Clause - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 5,502 - Commits in the last 12 months: 120 - Contributors: 205 - Last commit: Oct 1, 2026 - Latest release: v6.4.3 (Apr 24, 2026) - Install (npm): `npm install vega-lite`, 1.3M downloads per week - Topics: Grammar of graphics libraries ### Overview Vega-Lite is an open-source JavaScript visualization library released under the BSD-3-Clause license. Its GitHub repository has 5,502 stars, 722 forks, and 205 contributors. It is actively developed with 120 commits in the last 12 months. The latest release, v6.4.3, was published on Apr 24, 2026. On npm it is downloaded about 1.3M times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) ### Comparisons - [Vega-Altair vs Vega-Lite](https://awesomedataviz.com/compare/altair-vs-vega-lite/) Source: https://awesomedataviz.com/tools/vega-lite/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## LiveCharts2 > Animated, interactive charts, maps and gauges for .NET UI frameworks. - Category: [C# & .NET charting libraries](https://awesomedataviz.com/categories/dotnet/) - Website: https://livecharts.dev - Repository: https://github.com/Live-Charts/LiveCharts2 - License: MIT - Language: C# - Status: Active (commits in the last 90 days) - GitHub stars: 5,482 - Commits in the last 12 months: 1,374 - Contributors: 61 - Last commit: Jul 20, 2026 - Latest release: 2.0.4 (May 16, 2026) - Install (NuGet): `dotnet add package LiveChartsCore.SkiaSharpView`, 2.9M downloads in total ### Overview LiveCharts2 is an open-source .NET charting library released under the MIT license. Its GitHub repository has 5,482 stars, 712 forks, and 61 contributors. It is actively developed with 1,374 commits in the last 12 months. The latest release, 2.0.4, was published on May 16, 2026. It has been downloaded about 2.9M times from NuGet. ### Alternatives - [ScottPlot](https://awesomedataviz.com/tools/scottplot/): Interactive plotting library for .NET with WinForms, WPF, Avalonia, Blazor and other controls. (6.8K stars) - [OxyPlot](https://awesomedataviz.com/tools/oxyplot/): Cross-platform plotting library for .NET. (3.5K stars) - [Microcharts](https://awesomedataviz.com/tools/microcharts/): Simple cross-platform charts for .NET, drawn with SkiaSharp. (2.1K stars) - [Mapsui](https://awesomedataviz.com/tools/mapsui/): .NET map component for MAUI, Avalonia, Uno Platform, Blazor, WPF and WinUI. (1.6K stars) - [MSAGL](https://awesomedataviz.com/tools/msagl/): Microsoft Automatic Graph Layout: tools for graph layout and viewing in .NET. (1.5K stars) ### Comparisons - [LiveCharts2 vs ScottPlot](https://awesomedataviz.com/compare/livecharts2-vs-scottplot/) - [LiveCharts2 vs OxyPlot](https://awesomedataviz.com/compare/livecharts2-vs-oxyplot/) - [LiveCharts2 vs Microcharts](https://awesomedataviz.com/compare/livecharts2-vs-microcharts/) - [LiveCharts2 vs Mapsui](https://awesomedataviz.com/compare/livecharts2-vs-mapsui/) Source: https://awesomedataviz.com/tools/livecharts2/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Observable Plot > A JavaScript library for exploratory data visualization. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://observablehq.com/plot/ - Repository: https://github.com/observablehq/plot - License: ISC - Language: HTML - Status: Active (commits in the last 90 days) - GitHub stars: 5,400 - Commits in the last 12 months: 38 - Contributors: 28 - Last commit: Sep 1, 2026 - Latest release: v0.6.17 (Feb 14, 2025) - Install (npm): `npm install @observablehq/plot`, 928.3K downloads per week - Topics: Grammar of graphics libraries, Exploratory data analysis tools ### Overview Observable Plot is an open-source JavaScript charting library released under the ISC license. Its GitHub repository has 5,400 stars, 245 forks, and 28 contributors. It is actively developed with 38 commits in the last 12 months. The latest release, v0.6.17, was published on Feb 14, 2025. On npm it is downloaded about 928.3K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) ### Comparisons - [D3.js vs Observable Plot](https://awesomedataviz.com/compare/d3-vs-observable-plot/) Source: https://awesomedataviz.com/tools/observable-plot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## TOAST UI Chart > Complete library with support for legacy browsers. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: http://ui.toast.com/tui-chart/ - Repository: https://github.com/nhn/tui.chart - License: MIT - Language: TypeScript - Status: Archived (the repository is archived and read-only) - GitHub stars: 5,400 - Commits in the last 12 months: 0 - Contributors: 6 - Last commit: Jul 19, 2023 - Latest release: v4.6.1 (Dec 21, 2022) - Install (npm): `npm install @toast-ui/chart`, 6.2K downloads per week ### Overview TOAST UI Chart is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 5,400 stars, 318 forks, and 6 contributors. Its repository is archived on GitHub and no longer receives updates. The latest release, v4.6.1, was published on Dec 21, 2022. On npm it is downloaded about 6.2K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/toast-ui-chart/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## JointJS > SVG-based JavaScript diagramming library for interactive diagrams and graph editors. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Website: https://jointjs.com - Repository: https://github.com/clientIO/joint - License: MPL-2.0 - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 5,393 - Commits in the last 12 months: 151 - Contributors: 83 - Last commit: Oct 1, 2026 - Latest release: @joint/router-avoid@4.3.3 (Sep 4, 2026) - Install (npm): `npm install @joint/core`, 65K downloads per week - Topics: Graph & network visualization, Diagrams & diagrams as code ### Overview JointJS is an open-source JavaScript graph visualization library released under the MPL-2.0 license. Its GitHub repository has 5,393 stars, 893 forks, and 83 contributors. It is actively developed with 151 commits in the last 12 months. The latest release, @joint/router-avoid@4.3.3, was published on Sep 4, 2026. On npm it is downloaded about 65K times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) Source: https://awesomedataviz.com/tools/jointjs/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## go-diagrams > Diagram-as-code library for system architecture diagrams in Go, rendered with Graphviz. - Category: [Go charting & plotting libraries](https://awesomedataviz.com/categories/go/) - Repository: https://github.com/blushft/go-diagrams - License: MIT - Language: Go - Status: Inactive (no commits in over a year) - GitHub stars: 5,235 - Commits in the last 12 months: 0 - Contributors: 6 - Last commit: Mar 22, 2025 - Install (Go): `go get github.com/blushft/go-diagrams` - Topics: Diagrams & diagrams as code ### Overview go-diagrams is an open-source Go plotting library released under the MIT license. Its GitHub repository has 5,235 stars, 232 forks, and 6 contributors. It has not had a commit since Mar 22, 2025. ### Alternatives - [termui](https://awesomedataviz.com/tools/termui/): Terminal dashboard and widget library with charts, gauges, sparklines and more. (13.6K stars) - [go-echarts](https://awesomedataviz.com/tools/go-echarts/): Simple yet powerful data visualizing library for Go. (7.6K stars) - [asciigraph](https://awesomedataviz.com/tools/asciigraph/): Lightweight ASCII line graphs for command-line apps. (3.1K stars) - [termdash](https://awesomedataviz.com/tools/termdash/): Terminal-based dashboard library with line charts, bar charts, gauges and donuts. (3K stars) - [plot](https://awesomedataviz.com/tools/plot/): API for building and drawing plots in Go. (3K stars) - [svgo](https://awesomedataviz.com/tools/svgo/): Go Language Library for SVG generation. (2.3K stars) ### Comparisons - [go-diagrams vs termui](https://awesomedataviz.com/compare/go-diagrams-vs-termui/) - [go-diagrams vs go-echarts](https://awesomedataviz.com/compare/go-diagrams-vs-go-echarts/) - [asciigraph vs go-diagrams](https://awesomedataviz.com/compare/asciigraph-vs-go-diagrams/) - [go-diagrams vs termdash](https://awesomedataviz.com/compare/go-diagrams-vs-termdash/) Source: https://awesomedataviz.com/tools/go-diagrams/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## WilliamChart > Simple chart library. - Category: [Android chart libraries](https://awesomedataviz.com/categories/android/) - Repository: https://github.com/diogobernardino/williamchart - Language: Kotlin - Status: Maintained (commits in the last 12 months) - GitHub stars: 5,095 - Commits in the last 12 months: 2 - Contributors: 4 - Last commit: Oct 4, 2025 - Latest release: 3.10.1 (Jan 30, 2021) ### Overview WilliamChart is an Android chart library. Its GitHub repository has 5,095 stars, 788 forks, and 4 contributors. It is maintained with 2 commits in the last 12 months; the most recent commit was on Oct 4, 2025. The latest release, 3.10.1, was published on Jan 30, 2021. ### Alternatives - [MPAndroidChart](https://awesomedataviz.com/tools/mpandroidchart/): A powerful & easy to use chart library. (38.2K stars) - [HelloCharts](https://awesomedataviz.com/tools/hellocharts/): Android chart library with line, column, pie, bubble and combo charts, plus zoom and scroll. (7.6K stars) - [Vico](https://awesomedataviz.com/tools/vico/): Extensible chart library for Jetpack Compose and Compose Multiplatform. (3.2K stars) - [DecoView](https://awesomedataviz.com/tools/decoview/): Animated circular wheel chart library. (984 stars) ### Comparisons - [MPAndroidChart vs WilliamChart](https://awesomedataviz.com/compare/mpandroidchart-vs-williamchart/) - [HelloCharts vs WilliamChart](https://awesomedataviz.com/compare/hellocharts-vs-williamchart/) - [Vico vs WilliamChart](https://awesomedataviz.com/compare/vico-vs-williamchart/) - [DecoView vs WilliamChart](https://awesomedataviz.com/compare/decoview-vs-williamchart/) Source: https://awesomedataviz.com/tools/williamchart/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## echarts-for-react > React wrapper for Apache ECharts. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://git.hust.cc/echarts-for-react - Repository: https://github.com/hustcc/echarts-for-react - License: MIT - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 5,006 - Commits in the last 12 months: 4 - Contributors: 21 - Last commit: Jan 21, 2026 - Latest release: v3.0.5 (Nov 6, 2025) - Install (npm): `npm install echarts-for-react`, 1.8M downloads per week ### Overview echarts-for-react is an open-source React chart library released under the MIT license. Its GitHub repository has 5,006 stars, 648 forks, and 21 contributors. It is maintained with 4 commits in the last 12 months; the most recent commit was on Jan 21, 2026. The latest release, v3.0.5, was published on Nov 6, 2025. On npm it is downloaded about 1.8M times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) Source: https://awesomedataviz.com/tools/echarts-for-react/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Embedding Atlas > Interactive visualization of large embeddings with search, filtering and density views, by Apple. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Website: https://apple.github.io/embedding-atlas/ - Repository: https://github.com/apple/embedding-atlas - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 4,965 - Commits in the last 12 months: 134 - Contributors: 26 - Last commit: Oct 2, 2026 - Latest release: v0.25.0 (Oct 3, 2026) - Topics: Machine learning & AI visualization ### Overview Embedding Atlas is an open-source ML visualization tool released under the MIT license. Its GitHub repository has 4,965 stars, 329 forks, and 26 contributors. It is actively developed with 134 commits in the last 12 months. The latest release, v0.25.0, was published on Oct 3, 2026. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) Source: https://awesomedataviz.com/tools/embedding-atlas/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Epoch > Perfect to create real-time charts. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: http://epochjs.github.io/epoch - Repository: https://github.com/epochjs/epoch - License: MIT - Language: HTML - Status: Inactive (no commits in over a year) - GitHub stars: 4,942 - Commits in the last 12 months: 0 - Contributors: 17 - Last commit: Mar 15, 2016 - Topics: Time series & real-time charts ### Overview Epoch is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 4,942 stars, 274 forks, and 17 contributors. It has not had a commit since Mar 15, 2016. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/epoch/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Matplot++ > C++ graphics library for data visualization with a MATLAB-like API. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Website: https://alandefreitas.github.io/matplotplusplus/ - Repository: https://github.com/alandefreitas/matplotplusplus - License: MIT - Language: C++ - Status: Maintained (commits in the last 12 months) - GitHub stars: 4,937 - Commits in the last 12 months: 3 - Contributors: 50 - Last commit: Apr 2, 2026 - Latest release: v1.2.2 (Feb 14, 2025) - Topics: 3D & scientific visualization ### Overview Matplot++ is an open-source C++ visualization tool released under the MIT license. Its GitHub repository has 4,937 stars, 389 forks, and 50 contributors. It is maintained with 3 commits in the last 12 months; the most recent commit was on Apr 2, 2026. The latest release, v1.2.2, was published on Feb 14, 2025. ### Alternatives - [ImPlot](https://awesomedataviz.com/tools/implot/): Immediate-mode plotting library for Dear ImGui. (6.2K stars) - [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/): Open-source Qt5 application to plot charts (based on Qwt). (6.2K stars) - [F3D](https://awesomedataviz.com/tools/f3d/): Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. (4.7K stars) - [Mapnik](https://awesomedataviz.com/tools/mapnik/): Toolkit for rendering maps, widely used to render OpenStreetMap tiles. (4K stars) - [ROOT](https://awesomedataviz.com/tools/root/): CERN framework for analyzing, storing and visualizing large scientific datasets. (3.3K stars) - [VTK](https://awesomedataviz.com/tools/vtk/): Open-source library for 3d Graphics, image processing and visualization. (3.2K stars) ### Comparisons - [ImPlot vs Matplot++](https://awesomedataviz.com/compare/implot-vs-matplotpp/) - [Matplot++ vs PlotJuggler](https://awesomedataviz.com/compare/matplotpp-vs-plotjuggler/) - [F3D vs Matplot++](https://awesomedataviz.com/compare/f3d-vs-matplotpp/) - [Mapnik vs Matplot++](https://awesomedataviz.com/compare/mapnik-vs-matplotpp/) Source: https://awesomedataviz.com/tools/matplotpp/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## YouPlot > Command-line tool that draws plots in the terminal from piped data. - Category: [Ruby charting libraries](https://awesomedataviz.com/categories/ruby/) - Repository: https://github.com/red-data-tools/YouPlot - License: MIT - Language: Ruby - Status: Maintained (commits in the last 12 months) - GitHub stars: 4,857 - Commits in the last 12 months: 40 - Contributors: 11 - Last commit: Jun 22, 2026 - Latest release: v0.5.0 (May 24, 2026) - Install (RubyGems): `gem install youplot` - Topics: Terminal & command-line charts ### Overview YouPlot is an open-source Ruby charting library released under the MIT license. Its GitHub repository has 4,857 stars, 73 forks, and 11 contributors. It is maintained with 40 commits in the last 12 months; the most recent commit was on Jun 22, 2026. The latest release, v0.5.0, was published on May 24, 2026. ### Alternatives - [Chartkick](https://awesomedataviz.com/tools/chartkick/): Create charts with one line of Ruby. (6.5K stars) - [Blazer](https://awesomedataviz.com/tools/blazer/): Business intelligence tool for Rails apps: explore data with SQL and build charts and dashboards. (4.8K stars) - [Gruff](https://awesomedataviz.com/tools/gruff/): Graphing library for Ruby that renders charts as images using RMagick. (1.4K stars) ### Comparisons - [Chartkick vs YouPlot](https://awesomedataviz.com/compare/chartkick-vs-youplot/) - [Blazer vs YouPlot](https://awesomedataviz.com/compare/blazer-vs-youplot/) - [Gruff vs YouPlot](https://awesomedataviz.com/compare/gruff-vs-youplot/) Source: https://awesomedataviz.com/tools/youplot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Blazer > Business intelligence tool for Rails apps: explore data with SQL and build charts and dashboards. - Category: [Ruby charting libraries](https://awesomedataviz.com/categories/ruby/) - Repository: https://github.com/ankane/blazer - License: MIT - Language: Ruby - Status: Active (commits in the last 90 days) - GitHub stars: 4,802 - Commits in the last 12 months: 254 - Contributors: 48 - Last commit: Sep 25, 2026 - Install (RubyGems): `gem install blazer` - Topics: Dashboards & BI ### Overview Blazer is an open-source Ruby charting library released under the MIT license. Its GitHub repository has 4,802 stars, 501 forks, and 48 contributors. It is actively developed with 254 commits in the last 12 months. ### Alternatives - [Chartkick](https://awesomedataviz.com/tools/chartkick/): Create charts with one line of Ruby. (6.5K stars) - [YouPlot](https://awesomedataviz.com/tools/youplot/): Command-line tool that draws plots in the terminal from piped data. (4.9K stars) - [Gruff](https://awesomedataviz.com/tools/gruff/): Graphing library for Ruby that renders charts as images using RMagick. (1.4K stars) ### Comparisons - [Blazer vs Chartkick](https://awesomedataviz.com/compare/blazer-vs-chartkick/) - [Blazer vs YouPlot](https://awesomedataviz.com/compare/blazer-vs-youplot/) - [Blazer vs Gruff](https://awesomedataviz.com/compare/blazer-vs-gruff/) Source: https://awesomedataviz.com/tools/blazer/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## plotnine > Grammar of graphics for Python, based on R's ggplot2. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://plotnine.org - Repository: https://github.com/has2k1/plotnine - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 4,770 - Commits in the last 12 months: 490 - Contributors: 104 - Last commit: Sep 28, 2026 - Latest release: v0.15.8 (Aug 14, 2026) - Install (PyPI): `pip install plotnine`, 602.5K downloads per week - Topics: Grammar of graphics libraries ### Overview plotnine is an open-source Python visualization library released under the MIT license. Its GitHub repository has 4,770 stars, 255 forks, and 104 contributors. It is actively developed with 490 commits in the last 12 months. The latest release, v0.15.8, was published on Aug 14, 2026. On PyPI it is downloaded about 602.5K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) ### Comparisons - [ggplot2 vs plotnine](https://awesomedataviz.com/compare/ggplot2-vs-plotnine/) Source: https://awesomedataviz.com/tools/plotnine/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## F3D > Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Website: https://f3d.app - Repository: https://github.com/f3d-app/f3d - License: BSD-3-Clause - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 4,741 - Commits in the last 12 months: 696 - Contributors: 120 - Last commit: Oct 2, 2026 - Latest release: v3.5.0 (Apr 5, 2026) - Install (npm): `npm install f3d`, 1.6K downloads per week - Install (PyPI): `pip install f3d`, 309 downloads per week - Topics: 3D & scientific visualization ### Overview F3D is an open-source C++ visualization tool released under the BSD-3-Clause license. Its GitHub repository has 4,741 stars, 448 forks, and 120 contributors. It is actively developed with 696 commits in the last 12 months. The latest release, v3.5.0, was published on Apr 5, 2026. On npm it is downloaded about 1.6K times per week. ### Alternatives - [ImPlot](https://awesomedataviz.com/tools/implot/): Immediate-mode plotting library for Dear ImGui. (6.2K stars) - [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/): Open-source Qt5 application to plot charts (based on Qwt). (6.2K stars) - [Matplot++](https://awesomedataviz.com/tools/matplotpp/): C++ graphics library for data visualization with a MATLAB-like API. (4.9K stars) - [Mapnik](https://awesomedataviz.com/tools/mapnik/): Toolkit for rendering maps, widely used to render OpenStreetMap tiles. (4K stars) - [ROOT](https://awesomedataviz.com/tools/root/): CERN framework for analyzing, storing and visualizing large scientific datasets. (3.3K stars) - [VTK](https://awesomedataviz.com/tools/vtk/): Open-source library for 3d Graphics, image processing and visualization. (3.2K stars) ### Comparisons - [F3D vs ImPlot](https://awesomedataviz.com/compare/f3d-vs-implot/) - [F3D vs PlotJuggler](https://awesomedataviz.com/compare/f3d-vs-plotjuggler/) - [F3D vs Matplot++](https://awesomedataviz.com/compare/f3d-vs-matplotpp/) - [F3D vs Mapnik](https://awesomedataviz.com/compare/f3d-vs-mapnik/) Source: https://awesomedataviz.com/tools/f3d/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## RATH > Automatic Exploratory Data Analysis & Data Visualization tool which is powered by an AI-assisted Augmented Analytics engine. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://rath.kanaries.net - Repository: https://github.com/Kanaries/Rath - License: AGPL-3.0 - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 4,686 - Commits in the last 12 months: 29 - Contributors: 18 - Last commit: Aug 14, 2026 - Latest release: 2.1.0 (Aug 25, 2023) - Topics: Exploratory data analysis tools ### Overview RATH is an open-source data visualization app released under the AGPL-3.0 license. Its GitHub repository has 4,686 stars, 380 forks, and 18 contributors. It is actively developed with 29 commits in the last 12 months. The latest release, 2.1.0, was published on Aug 25, 2023. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/rath/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Plotters > Drawing library for data plotting in Rust, with bitmap, SVG, WebAssembly and GUI backends. - Category: [Rust plotting & visualization libraries](https://awesomedataviz.com/categories/rust/) - Website: https://plotters-rs.github.io/home/ - Repository: https://github.com/plotters-rs/plotters - License: MIT - Language: Rust - Status: Maintained (commits in the last 12 months) - GitHub stars: 4,632 - Commits in the last 12 months: 23 - Contributors: 102 - Last commit: Mar 17, 2026 - Install (crates.io): `cargo add plotters`, 53.4M downloads per 90 days - Topics: Time series & real-time charts ### Overview Plotters is an open-source Rust visualization library released under the MIT license. Its GitHub repository has 4,632 stars, 319 forks, and 102 contributors. It is maintained with 23 commits in the last 12 months; the most recent commit was on Mar 17, 2026. On crates.io it is downloaded about 53.4M times per 90 days. ### Alternatives - [Charming](https://awesomedataviz.com/tools/charming/): Chart rendering library for Rust powered by Apache ECharts. (2.6K stars) - [Plotly.rs](https://awesomedataviz.com/tools/plotly-rs/): Plotly.js-based interactive plotting library for Rust. (1.5K stars) - [malevich](https://awesomedataviz.com/tools/malevich/): Terminal plotting: line, scatter, bar, histogram, heatmap, box plot, violin and more, with automatic axes. (70 stars) ### Comparisons - [Charming vs Plotters](https://awesomedataviz.com/compare/charming-vs-plotters/) - [Plotly.rs vs Plotters](https://awesomedataviz.com/compare/plotly-rs-vs-plotters/) - [malevich vs Plotters](https://awesomedataviz.com/compare/malevich-vs-plotters/) Source: https://awesomedataviz.com/tools/plotters/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## maptalks.js > Pluggable JavaScript library for integrated 2D/3D maps. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://maptalks.org - Repository: https://github.com/maptalks/maptalks.js - License: BSD-3-Clause - Language: HTML - Status: Active (commits in the last 90 days) - GitHub stars: 4,534 - Commits in the last 12 months: 293 - Contributors: 62 - Last commit: Aug 25, 2026 - Latest release: maptalks-gpu@0.124.4 (Mar 4, 2026) - Install (npm): `npm install maptalks`, 7K downloads per week - Topics: Maps & geospatial visualization, 3D & scientific visualization ### Overview maptalks.js is an open-source JavaScript mapping library released under the BSD-3-Clause license. Its GitHub repository has 4,534 stars, 511 forks, and 62 contributors. It is actively developed with 293 commits in the last 12 months. The latest release, maptalks-gpu@0.124.4, was published on Mar 4, 2026. On npm it is downloaded about 7K times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/maptalks-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## mplfinance > Financial market data visualization (candlestick, OHLC, volume) using matplotlib. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://pypi.org/project/mplfinance/ - Repository: https://github.com/matplotlib/mplfinance - License: BSD-style - Language: Python - Status: Inactive (no commits in over a year) - GitHub stars: 4,439 - Commits in the last 12 months: 0 - Contributors: 39 - Last commit: Apr 2, 2024 - Latest release: v0.12.10b0 (Aug 2, 2023) - Install (PyPI): `pip install mplfinance`, 94.5K downloads per week - Topics: Financial & stock charts ### Overview mplfinance is a Python visualization library. Its GitHub repository has 4,439 stars, 678 forks, and 39 contributors. It has not had a commit since Apr 2, 2024. The latest release, v0.12.10b0, was published on Aug 2, 2023. On PyPI it is downloaded about 94.5K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/mplfinance/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## PyQtGraph > Interactive and realtime 2D/3D/Image plotting and science/engineering widgets. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://www.pyqtgraph.org/ - Repository: https://github.com/pyqtgraph/pyqtgraph - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 4,421 - Commits in the last 12 months: 355 - Contributors: 273 - Last commit: Oct 4, 2026 - Latest release: pyqtgraph-0.14.0 (Nov 16, 2025) - Install (PyPI): `pip install pyqtgraph`, 172.3K downloads per week - Topics: 3D & scientific visualization, Time series & real-time charts ### Overview PyQtGraph is an open-source Python visualization library released under the MIT license. Its GitHub repository has 4,421 stars, 1,184 forks, and 273 contributors. It is actively developed with 355 commits in the last 12 months. The latest release, pyqtgraph-0.14.0, was published on Nov 16, 2025. On PyPI it is downloaded about 172.3K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/pyqtgraph/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Yellowbrick > Visual analysis and diagnostic tools for machine learning model selection with scikit-learn. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Website: http://www.scikit-yb.org/ - Repository: https://github.com/DistrictDataLabs/yellowbrick - License: Apache-2.0 - Language: Python - Status: Inactive (no commits in over a year) - GitHub stars: 4,407 - Commits in the last 12 months: 0 - Contributors: 109 - Last commit: Jul 5, 2023 - Latest release: v1.5 (Aug 21, 2022) - Topics: Machine learning & AI visualization ### Overview Yellowbrick is an open-source ML visualization tool released under the Apache-2.0 license. Its GitHub repository has 4,407 stars, 570 forks, and 109 contributors. It has not had a commit since Jul 5, 2023. The latest release, v1.5, was published on Aug 21, 2022. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) Source: https://awesomedataviz.com/tools/yellowbrick/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ngx-charts > Declarative charting framework for Angular, using D3 for math and Angular for rendering. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://swimlane.github.io/ngx-charts/ - Repository: https://github.com/swimlane/ngx-charts - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 4,363 - Commits in the last 12 months: 19 - Contributors: 123 - Last commit: Sep 3, 2026 - Install (npm): `npm install @swimlane/ngx-charts`, 195.9K downloads per week ### Overview ngx-charts is an open-source JavaScript visualization library released under the MIT license. Its GitHub repository has 4,363 stars, 1,162 forks, and 123 contributors. It is actively developed with 19 commits in the last 12 months. On npm it is downloaded about 195.9K times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) Source: https://awesomedataviz.com/tools/ngx-charts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Kroki > Unified API that renders diagrams from many text formats, including PlantUML, Mermaid, Graphviz and D2. - Category: [Diagrams as code](https://awesomedataviz.com/categories/diagrams-as-code/) - Website: https://kroki.io - Repository: https://github.com/yuzutech/kroki - License: MIT - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 4,358 - Commits in the last 12 months: 204 - Contributors: 84 - Last commit: Sep 28, 2026 - Latest release: v0.32.1 (Aug 12, 2026) - Topics: Diagrams & diagrams as code ### Overview Kroki is an open-source diagram-as-code tool released under the MIT license. Its GitHub repository has 4,358 stars, 321 forks, and 84 contributors. It is actively developed with 204 commits in the last 12 months. The latest release, v0.32.1, was published on Aug 12, 2026. ### Alternatives - [Mermaid](https://awesomedataviz.com/tools/mermaid/): Generate diagrams and flowcharts from markdown-like text definitions, with a live editor. (90.5K stars) - [Diagrams](https://awesomedataviz.com/tools/diagrams/): Diagram as code in Python for prototyping cloud system architectures. (42.7K stars) - [D2](https://awesomedataviz.com/tools/d2/): Declarative diagram scripting language that turns text into diagrams. (25.6K stars) - [PlantUML](https://awesomedataviz.com/tools/plantuml/): Generates UML, Gantt, mind map and other diagrams from plain text. (13.4K stars) - [Markmap](https://awesomedataviz.com/tools/markmap/): Builds interactive mind maps from Markdown. (13.1K stars) - [flowchart.js](https://awesomedataviz.com/tools/flowchart-js/): Draws SVG flowcharts from a textual description. (8.7K stars) Source: https://awesomedataviz.com/tools/kroki/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## missingno > Provides flexible toolset of data-visualization utilities that allows quick visual summary of the completeness of your dataset, based on matplotlib. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Repository: https://github.com/ResidentMario/missingno - License: MIT - Language: Python - Status: Inactive (no commits in over a year) - GitHub stars: 4,211 - Commits in the last 12 months: 0 - Contributors: 16 - Last commit: Feb 26, 2023 - Latest release: 0.5.2 (Feb 26, 2023) - Install (PyPI): `pip install missingno`, 61.1K downloads per week ### Overview missingno is an open-source Python visualization library released under the MIT license. Its GitHub repository has 4,211 stars, 520 forks, and 16 contributors. It has not had a commit since Feb 26, 2023. The latest release, 0.5.2, was published on Feb 26, 2023. On PyPI it is downloaded about 61.1K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/missingno/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## L7 > Large-scale WebGL-powered Geospatial Data Visualization analysis framework, maintained by Alibaba - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://l7.antv.antgroup.com - Repository: https://github.com/antvis/L7 - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 4,070 - Commits in the last 12 months: 112 - Contributors: 62 - Last commit: Jul 30, 2026 - Latest release: v2.22.5 (Mar 11, 2025) - Install (npm): `npm install @antv/l7`, 29.4K downloads per week - Topics: Maps & geospatial visualization, 3D & scientific visualization, GPU-accelerated & WebGL visualization, Visualizing large datasets ### Overview L7 is an open-source JavaScript mapping library released under the MIT license. Its GitHub repository has 4,070 stars, 656 forks, and 62 contributors. It is actively developed with 112 commits in the last 12 months. The latest release, v2.22.5, was published on Mar 11, 2025. On npm it is downloaded about 29.4K times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/l7/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Mapnik > Toolkit for rendering maps, widely used to render OpenStreetMap tiles. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Website: http://mapnik.org - Repository: https://github.com/mapnik/mapnik - License: LGPL-2.1 - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 3,965 - Commits in the last 12 months: 191 - Contributors: 98 - Last commit: Sep 23, 2026 - Latest release: v4.3.2 (Sep 23, 2026) - Topics: Maps & geospatial visualization ### Overview Mapnik is an open-source C++ visualization tool released under the LGPL-2.1 license. Its GitHub repository has 3,965 stars, 839 forks, and 98 contributors. It is actively developed with 191 commits in the last 12 months. The latest release, v4.3.2, was published on Sep 23, 2026. ### Alternatives - [ImPlot](https://awesomedataviz.com/tools/implot/): Immediate-mode plotting library for Dear ImGui. (6.2K stars) - [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/): Open-source Qt5 application to plot charts (based on Qwt). (6.2K stars) - [Matplot++](https://awesomedataviz.com/tools/matplotpp/): C++ graphics library for data visualization with a MATLAB-like API. (4.9K stars) - [F3D](https://awesomedataviz.com/tools/f3d/): Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. (4.7K stars) - [ROOT](https://awesomedataviz.com/tools/root/): CERN framework for analyzing, storing and visualizing large scientific datasets. (3.3K stars) - [VTK](https://awesomedataviz.com/tools/vtk/): Open-source library for 3d Graphics, image processing and visualization. (3.2K stars) ### Comparisons - [ImPlot vs Mapnik](https://awesomedataviz.com/compare/implot-vs-mapnik/) - [Mapnik vs PlotJuggler](https://awesomedataviz.com/compare/mapnik-vs-plotjuggler/) - [Mapnik vs Matplot++](https://awesomedataviz.com/compare/mapnik-vs-matplotpp/) - [F3D vs Mapnik](https://awesomedataviz.com/compare/f3d-vs-mapnik/) Source: https://awesomedataviz.com/tools/mapnik/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## VivaGraph > Graph drawing library for JavaScript. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Repository: https://github.com/anvaka/VivaGraphJS - License: BSD-3-Clause - Language: JavaScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 3,862 - Commits in the last 12 months: 1 - Contributors: 16 - Last commit: Mar 6, 2026 - Install (npm): `npm install vivagraphjs`, 1.9K downloads per week - Topics: Graph & network visualization, GPU-accelerated & WebGL visualization ### Overview VivaGraph is an open-source JavaScript graph visualization library released under the BSD-3-Clause license. Its GitHub repository has 3,862 stars, 418 forks, and 16 contributors. It is maintained with 1 commit in the last 12 months; the most recent commit was on Mar 6, 2026. On npm it is downloaded about 1.9K times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) Source: https://awesomedataviz.com/tools/vivagraph/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## PyVista > 3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit (VTK) - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://docs.pyvista.org - Repository: https://github.com/pyvista/pyvista - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 3,832 - Commits in the last 12 months: 884 - Contributors: 210 - Last commit: Oct 4, 2026 - Latest release: v0.49.0 (Sep 8, 2026) - Install (PyPI): `pip install pyvista`, 257.4K downloads per week - Topics: 3D & scientific visualization ### Overview PyVista is an open-source Python visualization library released under the MIT license. Its GitHub repository has 3,832 stars, 660 forks, and 210 contributors. It is actively developed with 884 commits in the last 12 months. The latest release, v0.49.0, was published on Sep 8, 2026. On PyPI it is downloaded about 257.4K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/pyvista/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## DataMaps > Interactive SVG maps using D3.js. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: http://datamaps.github.io - Repository: https://github.com/markmarkoh/datamaps - License: MIT - Language: JavaScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 3,797 - Commits in the last 12 months: 1 - Contributors: 39 - Last commit: Feb 10, 2026 - Latest release: v0.5.0 (Mar 14, 2016) - Install (npm): `npm install datamaps`, 68.3K downloads per week - Topics: Maps & geospatial visualization ### Overview DataMaps is an open-source JavaScript mapping library released under the MIT license. Its GitHub repository has 3,797 stars, 997 forks, and 39 contributors. It is maintained with 1 commit in the last 12 months; the most recent commit was on Feb 10, 2026. The latest release, v0.5.0, was published on Mar 14, 2016. On npm it is downloaded about 68.3K times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/datamaps/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## leafmap > Interactive mapping and geospatial analysis in Jupyter with multiple mapping backends. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://leafmap.org - Repository: https://github.com/opengeos/leafmap - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 3,782 - Commits in the last 12 months: 147 - Contributors: 46 - Last commit: Sep 20, 2026 - Latest release: v0.63.1 (Aug 2, 2026) - Install (PyPI): `pip install leafmap`, 7.3K downloads per week - Topics: Maps & geospatial visualization, Jupyter & notebook visualization ### Overview leafmap is an open-source Python visualization library released under the MIT license. Its GitHub repository has 3,782 stars, 474 forks, and 46 contributors. It is actively developed with 147 commits in the last 12 months. The latest release, v0.63.1, was published on Aug 2, 2026. On PyPI it is downloaded about 7.3K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/leafmap/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## bqplot > Plotting library for IPython/Jupyter notebooks. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://bqplot.github.io/bqplot - Repository: https://github.com/bqplot/bqplot - License: Apache-2.0 - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 3,693 - Commits in the last 12 months: 21 - Contributors: 59 - Last commit: May 7, 2026 - Latest release: 0.13.1 (May 7, 2026) - Install (PyPI): `pip install bqplot`, 47.6K downloads per week - Topics: Jupyter & notebook visualization ### Overview bqplot is an open-source Python visualization library released under the Apache-2.0 license. Its GitHub repository has 3,693 stars, 477 forks, and 59 contributors. It is maintained with 21 commits in the last 12 months; the most recent commit was on May 7, 2026. The latest release, 0.13.1, was published on May 7, 2026. On PyPI it is downloaded about 47.6K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/bqplot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## JBChartView > Charting library for both line and bar graphs. - Category: [iOS & Swift chart libraries](https://awesomedataviz.com/categories/ios/) - Repository: https://github.com/Jawbone/JBChartView - License: Other - Language: Objective-C - Status: Inactive (no commits in over a year) - GitHub stars: 3,693 - Commits in the last 12 months: 0 - Contributors: 23 - Last commit: Feb 8, 2017 ### Overview JBChartView is an iOS chart library. Its GitHub repository has 3,693 stars, 402 forks, and 23 contributors. It has not had a commit since Feb 8, 2017. ### Alternatives - [Charts](https://awesomedataviz.com/tools/charts/): IOS port of MPAndroidChart. You can create charts for both platforms with very similar code. (28K stars) - [PNChart](https://awesomedataviz.com/tools/pnchart/): A simple and beautiful chart lib used in Piner and CoinsMan. (9.6K stars) - [ChartView](https://awesomedataviz.com/tools/chartview/): Line, bar and pie chart views built with SwiftUI. (5.6K stars) - [Core Plot](https://awesomedataviz.com/tools/core-plot/): 2D plotting framework for macOS, iOS and tvOS. (2.8K stars) - [BEMSimpleLineGraph](https://awesomedataviz.com/tools/bemsimplelinegraph/): Highly customizable and interactive line graphs. (2.6K stars) - [SwiftCharts](https://awesomedataviz.com/tools/swiftcharts/): Customizable charts library for iOS. (2.6K stars) ### Comparisons - [Charts vs JBChartView](https://awesomedataviz.com/compare/charts-vs-jbchartview/) - [JBChartView vs PNChart](https://awesomedataviz.com/compare/jbchartview-vs-pnchart/) - [ChartView vs JBChartView](https://awesomedataviz.com/compare/chartview-vs-jbchartview/) - [Core Plot vs JBChartView](https://awesomedataviz.com/compare/core-plot-vs-jbchartview/) Source: https://awesomedataviz.com/tools/jbchartview/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ggpy > Plotting system based on R's ggplot2. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: http://yhat.github.io/ggpy/ - Repository: https://github.com/yhat/ggpy - License: BSD-2-Clause - Language: Python - Status: Archived (the repository is archived and read-only) - GitHub stars: 3,688 - Commits in the last 12 months: 0 - Contributors: 12 - Last commit: Nov 20, 2016 - Install (PyPI): `pip install ggplot`, 15.4K downloads per week - Topics: Grammar of graphics libraries ### Overview ggpy is an open-source Python visualization library released under the BSD-2-Clause license. Its GitHub repository has 3,688 stars, 559 forks, and 12 contributors. Its repository is archived on GitHub and no longer receives updates. On PyPI it is downloaded about 15.4K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/ggpy/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## LIT > Learning Interpretability Tool: interactive visual analysis of ML model behavior, by Google PAIR. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Website: https://pair-code.github.io/lit - Repository: https://github.com/PAIR-code/lit - License: Apache-2.0 - Language: TypeScript - Status: Inactive (no commits in over a year) - GitHub stars: 3,668 - Commits in the last 12 months: 0 - Contributors: 37 - Last commit: Dec 20, 2024 - Latest release: v1.3.1 (Dec 20, 2024) - Install (PyPI): `pip install lit-nlp`, 1.3K downloads per week - Topics: Machine learning & AI visualization ### Overview LIT is an open-source ML visualization tool released under the Apache-2.0 license. Its GitHub repository has 3,668 stars, 366 forks, and 37 contributors. It has not had a commit since Dec 20, 2024. The latest release, v1.3.1, was published on Dec 20, 2024. On PyPI it is downloaded about 1.3K times per week. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) Source: https://awesomedataviz.com/tools/lit/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Observable Framework > Static site generator for data apps, dashboards and reports using JavaScript, SQL and Markdown. - Category: [Open-source dashboards & BI tools](https://awesomedataviz.com/categories/dashboards-and-bi/) - Website: https://observablehq.com/framework/ - Repository: https://github.com/observablehq/framework - License: ISC - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 3,657 - Commits in the last 12 months: 12 - Contributors: 38 - Last commit: May 15, 2026 - Latest release: v1.13.4 (Mar 2, 2026) - Install (npm): `npm install @observablehq/framework`, 13.3K downloads per week - Topics: Dashboards & BI ### Overview Observable Framework is an open-source dashboard and BI tool released under the ISC license. Its GitHub repository has 3,657 stars, 205 forks, and 38 contributors. It is maintained with 12 commits in the last 12 months; the most recent commit was on May 15, 2026. The latest release, v1.13.4, was published on Mar 2, 2026. On npm it is downloaded about 13.3K times per week. ### Alternatives - [Grafana](https://awesomedataviz.com/tools/grafana/): Observability and data visualization platform for metrics, logs and traces from many data sources. (77.1K stars) - [Apache Superset](https://awesomedataviz.com/tools/superset/): Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. (75K stars) - [Metabase](https://awesomedataviz.com/tools/metabase/): Business intelligence tool for querying data and building dashboards, with embedded analytics. (49.5K stars) - [Redash](https://awesomedataviz.com/tools/redash/): Query data sources with SQL, then visualize the results and build dashboards. (28.8K stars) - [Kibana](https://awesomedataviz.com/tools/kibana/): Visualization and dashboard UI for data stored in Elasticsearch. (21.3K stars) - [Evidence](https://awesomedataviz.com/tools/evidence/): Business intelligence as code: build reports and dashboards with SQL and Markdown. (7K stars) Source: https://awesomedataviz.com/tools/observable-framework/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Chartify > Bokeh wrapper that makes it easy for data scientists to create charts. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Repository: https://github.com/spotify/chartify - License: Apache-2.0 - Language: Python - Status: Inactive (no commits in over a year) - GitHub stars: 3,653 - Commits in the last 12 months: 0 - Contributors: 19 - Last commit: Oct 16, 2024 - Latest release: 5.0.1 (Oct 16, 2024) - Install (PyPI): `pip install chartify`, 426 downloads per week ### Overview Chartify is an open-source Python visualization library released under the Apache-2.0 license. Its GitHub repository has 3,653 stars, 336 forks, and 19 contributors. It has not had a commit since Oct 16, 2024. The latest release, 5.0.1, was published on Oct 16, 2024. On PyPI it is downloaded about 426 times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/chartify/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Vis.js > A dynamic visualization library including timeline, networks and graphs (2D and 3D). - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://visjs.org/ - Repository: https://github.com/visjs/vis-network - License: Apache-2.0 - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 3,632 - Commits in the last 12 months: 246 - Contributors: 127 - Last commit: Sep 13, 2026 - Latest release: v10.1.2 (Aug 19, 2026) - Install (npm): `npm install vis-network`, 974.5K downloads per week - Topics: Graph & network visualization, Time series & real-time charts ### Overview Vis.js is an open-source JavaScript visualization library released under the Apache-2.0 license. Its GitHub repository has 3,632 stars, 413 forks, and 127 contributors. It is actively developed with 246 commits in the last 12 months. The latest release, v10.1.2, was published on Aug 19, 2026. On npm it is downloaded about 974.5K times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) Source: https://awesomedataviz.com/tools/vis-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## VisPy > High-performance scientific visualization based on OpenGL. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://vispy.org/ - Repository: https://github.com/vispy/vispy - License: BSD-3-Clause - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 3,603 - Commits in the last 12 months: 62 - Contributors: 174 - Last commit: Sep 15, 2026 - Latest release: v0.17.0 (Sep 8, 2026) - Install (PyPI): `pip install vispy`, 147.8K downloads per week - Topics: 3D & scientific visualization, GPU-accelerated & WebGL visualization ### Overview VisPy is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 3,603 stars, 635 forks, and 174 contributors. It is actively developed with 62 commits in the last 12 months. The latest release, v0.17.0, was published on Sep 8, 2026. On PyPI it is downloaded about 147.8K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/vispy/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Datashader > Renders very large datasets into accurate images by rasterizing them. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: http://datashader.org - Repository: https://github.com/holoviz/datashader - License: BSD-3-Clause - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 3,562 - Commits in the last 12 months: 48 - Contributors: 61 - Last commit: Oct 2, 2026 - Latest release: v0.19.1 (May 19, 2026) - Install (PyPI): `pip install datashader`, 79.4K downloads per week - Topics: Visualizing large datasets ### Overview Datashader is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 3,562 stars, 378 forks, and 61 contributors. It is actively developed with 48 commits in the last 12 months. The latest release, v0.19.1, was published on May 19, 2026. On PyPI it is downloaded about 79.4K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/datashader/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## OxyPlot > Cross-platform plotting library for .NET. - Category: [C# & .NET charting libraries](https://awesomedataviz.com/categories/dotnet/) - Website: https://oxyplot.github.io/ - Repository: https://github.com/oxyplot/oxyplot - License: MIT - Language: C# - Status: Active (commits in the last 90 days) - GitHub stars: 3,541 - Commits in the last 12 months: 1 - Contributors: 125 - Last commit: Jul 14, 2026 - Latest release: v2.2.0 (Sep 20, 2024) - Install (NuGet): `dotnet add package OxyPlot.Core`, 10M downloads in total ### Overview OxyPlot is an open-source .NET charting library released under the MIT license. Its GitHub repository has 3,541 stars, 978 forks, and 125 contributors. It is actively developed with 1 commit in the last 12 months. The latest release, v2.2.0, was published on Sep 20, 2024. It has been downloaded about 10M times from NuGet. ### Alternatives - [ScottPlot](https://awesomedataviz.com/tools/scottplot/): Interactive plotting library for .NET with WinForms, WPF, Avalonia, Blazor and other controls. (6.8K stars) - [LiveCharts2](https://awesomedataviz.com/tools/livecharts2/): Animated, interactive charts, maps and gauges for .NET UI frameworks. (5.5K stars) - [Microcharts](https://awesomedataviz.com/tools/microcharts/): Simple cross-platform charts for .NET, drawn with SkiaSharp. (2.1K stars) - [Mapsui](https://awesomedataviz.com/tools/mapsui/): .NET map component for MAUI, Avalonia, Uno Platform, Blazor, WPF and WinUI. (1.6K stars) - [MSAGL](https://awesomedataviz.com/tools/msagl/): Microsoft Automatic Graph Layout: tools for graph layout and viewing in .NET. (1.5K stars) ### Comparisons - [OxyPlot vs ScottPlot](https://awesomedataviz.com/compare/oxyplot-vs-scottplot/) - [LiveCharts2 vs OxyPlot](https://awesomedataviz.com/compare/livecharts2-vs-oxyplot/) - [Microcharts vs OxyPlot](https://awesomedataviz.com/compare/microcharts-vs-oxyplot/) - [Mapsui vs OxyPlot](https://awesomedataviz.com/compare/mapsui-vs-oxyplot/) Source: https://awesomedataviz.com/tools/oxyplot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## WaveDrom > Draws timing diagrams and waveforms from simple textual descriptions. - Category: [Diagrams as code](https://awesomedataviz.com/categories/diagrams-as-code/) - Website: https://wavedrom.com/ - Repository: https://github.com/wavedrom/wavedrom - License: MIT - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 3,501 - Commits in the last 12 months: 12 - Contributors: 15 - Last commit: Aug 31, 2026 - Latest release: v2.1.2 (May 28, 2019) - Install (npm): `npm install wavedrom`, 55.6K downloads per week - Topics: Diagrams & diagrams as code ### Overview WaveDrom is an open-source diagram-as-code tool released under the MIT license. Its GitHub repository has 3,501 stars, 422 forks, and 15 contributors. It is actively developed with 12 commits in the last 12 months. The latest release, v2.1.2, was published on May 28, 2019. On npm it is downloaded about 55.6K times per week. ### Alternatives - [Mermaid](https://awesomedataviz.com/tools/mermaid/): Generate diagrams and flowcharts from markdown-like text definitions, with a live editor. (90.5K stars) - [Diagrams](https://awesomedataviz.com/tools/diagrams/): Diagram as code in Python for prototyping cloud system architectures. (42.7K stars) - [D2](https://awesomedataviz.com/tools/d2/): Declarative diagram scripting language that turns text into diagrams. (25.6K stars) - [PlantUML](https://awesomedataviz.com/tools/plantuml/): Generates UML, Gantt, mind map and other diagrams from plain text. (13.4K stars) - [Markmap](https://awesomedataviz.com/tools/markmap/): Builds interactive mind maps from Markdown. (13.1K stars) - [flowchart.js](https://awesomedataviz.com/tools/flowchart-js/): Draws SVG flowcharts from a textual description. (8.7K stars) Source: https://awesomedataviz.com/tools/wavedrom/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## TensorWatch > Debugging and visualization tool for data science and machine learning - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Repository: https://github.com/microsoft/tensorwatch - License: MIT - Language: Jupyter Notebook - Status: Maintained (commits in the last 12 months) - GitHub stars: 3,474 - Commits in the last 12 months: 6 - Contributors: 13 - Last commit: Mar 30, 2026 - Install (PyPI): `pip install tensorwatch`, 155 downloads per week - Topics: Machine learning & AI visualization ### Overview TensorWatch is an open-source ML visualization tool released under the MIT license. Its GitHub repository has 3,474 stars, 361 forks, and 13 contributors. It is maintained with 6 commits in the last 12 months; the most recent commit was on Mar 30, 2026. On PyPI it is downloaded about 155 times per week. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) Source: https://awesomedataviz.com/tools/tensorwatch/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## React Simple Maps > Composable SVG map charts for React, based on d3-geo and TopoJSON. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://www.react-simple-maps.io - Repository: https://github.com/zcreativelabs/react-simple-maps - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 3,379 - Commits in the last 12 months: 18 - Contributors: 22 - Last commit: Sep 12, 2026 - Install (npm): `npm install react-simple-maps`, 1.2M downloads per week - Topics: Maps & geospatial visualization ### Overview React Simple Maps is an open-source JavaScript mapping library released under the MIT license. Its GitHub repository has 3,379 stars, 464 forks, and 22 contributors. It is actively developed with 18 commits in the last 12 months. On npm it is downloaded about 1.2M times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/react-simple-maps/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ROOT > CERN framework for analyzing, storing and visualizing large scientific datasets. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Website: https://root.cern - Repository: https://github.com/root-project/root - License: Other - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 3,307 - Commits in the last 12 months: 4,406 - Contributors: 323 - Last commit: Oct 4, 2026 - Latest release: v6-40-04 (Aug 27, 2026) - Topics: Visualizing large datasets ### Overview ROOT is a C++ visualization tool. Its GitHub repository has 3,307 stars, 1,574 forks, and 323 contributors. It is actively developed with 4,406 commits in the last 12 months. The latest release, v6-40-04, was published on Aug 27, 2026. ### Alternatives - [ImPlot](https://awesomedataviz.com/tools/implot/): Immediate-mode plotting library for Dear ImGui. (6.2K stars) - [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/): Open-source Qt5 application to plot charts (based on Qwt). (6.2K stars) - [Matplot++](https://awesomedataviz.com/tools/matplotpp/): C++ graphics library for data visualization with a MATLAB-like API. (4.9K stars) - [F3D](https://awesomedataviz.com/tools/f3d/): Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. (4.7K stars) - [Mapnik](https://awesomedataviz.com/tools/mapnik/): Toolkit for rendering maps, widely used to render OpenStreetMap tiles. (4K stars) - [VTK](https://awesomedataviz.com/tools/vtk/): Open-source library for 3d Graphics, image processing and visualization. (3.2K stars) Source: https://awesomedataviz.com/tools/root/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Graphic Walker > An embeddable React component that functions as an open source alternative to Tableau, which allows data scientists to analyze data and visualize patterns with simple drag-and-drop operations. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://kanaries.net/graphic-walker - Repository: https://github.com/Kanaries/graphic-walker - License: Apache-2.0 - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 3,257 - Commits in the last 12 months: 51 - Contributors: 23 - Last commit: Oct 1, 2026 - Latest release: v0.5.0 (Nov 27, 2025) - Install (npm): `npm install @kanaries/graphic-walker`, 5.2K downloads per week - Topics: Dashboards & BI, Exploratory data analysis tools ### Overview Graphic Walker is an open-source React chart library released under the Apache-2.0 license. Its GitHub repository has 3,257 stars, 190 forks, and 23 contributors. It is actively developed with 51 commits in the last 12 months. The latest release, v0.5.0, was published on Nov 27, 2025. On npm it is downloaded about 5.2K times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) Source: https://awesomedataviz.com/tools/graphic-walker/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Dygraphs > Interactive line charts library that works with huge datasets. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://dygraphs.com/ - Repository: https://github.com/danvk/dygraphs - License: MIT - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 3,243 - Commits in the last 12 months: 54 - Contributors: 101 - Last commit: Jul 29, 2026 - Latest release: v2.2.2 (Jul 27, 2026) - Install (npm): `npm install dygraphs`, 20.3K downloads per week - Topics: Visualizing large datasets, Time series & real-time charts ### Overview Dygraphs is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 3,243 stars, 588 forks, and 101 contributors. It is actively developed with 54 commits in the last 12 months. The latest release, v2.2.2, was published on Jul 27, 2026. On npm it is downloaded about 20.3K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/dygraphs/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Timeline.js > Create interactive timelines. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://timeline.knightlab.com/ - Repository: https://github.com/NUKnightLab/TimelineJS3 - License: MPL-2.0 - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 3,224 - Commits in the last 12 months: 57 - Contributors: 45 - Last commit: Sep 22, 2026 - Install (npm): `npm install @knight-lab/timelinejs`, 6.4K downloads per week - Topics: Time series & real-time charts ### Overview Timeline.js is an open-source JavaScript visualization library released under the MPL-2.0 license. Its GitHub repository has 3,224 stars, 644 forks, and 45 contributors. It is actively developed with 57 commits in the last 12 months. On npm it is downloaded about 6.4K times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) Source: https://awesomedataviz.com/tools/timeline-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## VTK > Open-source library for 3d Graphics, image processing and visualization. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/), [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://gitlab.kitware.com/vtk/vtk - Repository: https://github.com/Kitware/VTK - License: BSD - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 3,211 - Commits in the last 12 months: 5,558 - Contributors: 257 - Last commit: Oct 4, 2026 - Install (PyPI): `pip install vtk`, 737.5K downloads per week - Topics: 3D & scientific visualization ### Overview VTK is an open-source C++ visualization tool released under the BSD license. Its GitHub repository has 3,211 stars, 1,309 forks, and 257 contributors. It is actively developed with 5,558 commits in the last 12 months. On PyPI it is downloaded about 737.5K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/vtk/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## globe.gl > UI component for globe data visualization using Three.js/WebGL. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://vasturiano.github.io/globe.gl/example/world-population/ - Repository: https://github.com/vasturiano/globe.gl - License: MIT - Language: HTML - Status: Active (commits in the last 90 days) - GitHub stars: 3,190 - Commits in the last 12 months: 20 - Contributors: 7 - Last commit: Aug 22, 2026 - Install (npm): `npm install globe.gl`, 246.6K downloads per week - Topics: Maps & geospatial visualization, GPU-accelerated & WebGL visualization ### Overview globe.gl is an open-source JavaScript mapping library released under the MIT license. Its GitHub repository has 3,190 stars, 434 forks, and 7 contributors. It is actively developed with 20 commits in the last 12 months. On npm it is downloaded about 246.6K times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/globe-gl/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Vico > Extensible chart library for Jetpack Compose and Compose Multiplatform. - Category: [Android chart libraries](https://awesomedataviz.com/categories/android/) - Website: https://guide.vico.patrykandpatrick.com - Repository: https://github.com/patrykandpatrick/vico - License: Apache-2.0 - Language: Kotlin - Status: Active (commits in the last 90 days) - GitHub stars: 3,185 - Commits in the last 12 months: 521 - Contributors: 30 - Last commit: Sep 25, 2026 - Latest release: v3.3.1 (Aug 28, 2026) - Install (Maven Central): `implementation("com.patrykandpatrick.vico:compose:2.1.3")` ### Overview Vico is an open-source Android chart library released under the Apache-2.0 license. Its GitHub repository has 3,185 stars, 204 forks, and 30 contributors. It is actively developed with 521 commits in the last 12 months. The latest release, v3.3.1, was published on Aug 28, 2026. ### Alternatives - [MPAndroidChart](https://awesomedataviz.com/tools/mpandroidchart/): A powerful & easy to use chart library. (38.2K stars) - [HelloCharts](https://awesomedataviz.com/tools/hellocharts/): Android chart library with line, column, pie, bubble and combo charts, plus zoom and scroll. (7.6K stars) - [WilliamChart](https://awesomedataviz.com/tools/williamchart/): Simple chart library. (5.1K stars) - [DecoView](https://awesomedataviz.com/tools/decoview/): Animated circular wheel chart library. (984 stars) ### Comparisons - [MPAndroidChart vs Vico](https://awesomedataviz.com/compare/mpandroidchart-vs-vico/) - [HelloCharts vs Vico](https://awesomedataviz.com/compare/hellocharts-vs-vico/) - [Vico vs WilliamChart](https://awesomedataviz.com/compare/vico-vs-williamchart/) - [DecoView vs Vico](https://awesomedataviz.com/compare/decoview-vs-vico/) Source: https://awesomedataviz.com/tools/vico/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## dtreeviz > Decision tree visualization and model interpretation library for Python. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Repository: https://github.com/parrt/dtreeviz - License: MIT - Language: Jupyter Notebook - Status: Maintained (commits in the last 12 months) - GitHub stars: 3,159 - Commits in the last 12 months: 18 - Contributors: 26 - Last commit: Jan 2, 2026 - Latest release: 2.3.1 (Dec 27, 2025) - Install (PyPI): `pip install dtreeviz`, 11K downloads per week - Topics: Machine learning & AI visualization ### Overview dtreeviz is an open-source ML visualization tool released under the MIT license. Its GitHub repository has 3,159 stars, 337 forks, and 26 contributors. It is maintained with 18 commits in the last 12 months; the most recent commit was on Jan 2, 2026. The latest release, 2.3.1, was published on Dec 27, 2025. On PyPI it is downloaded about 11K times per week. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) Source: https://awesomedataviz.com/tools/dtreeviz/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## React Native Chart Kit > Line, bar, pie, progress and contribution graph charts for React Native. - Category: [React Native chart libraries](https://awesomedataviz.com/categories/react-native/) - Website: https://chartkit.io - Repository: https://github.com/chart-kit/react-native-chart-kit - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 3,112 - Commits in the last 12 months: 131 - Contributors: 99 - Last commit: Sep 6, 2026 - Latest release: v7.0.4 (Sep 6, 2026) - Install (npm): `npm install react-native-chart-kit`, 135.6K downloads per week ### Overview React Native Chart Kit is an open-source React Native chart library released under the MIT license. Its GitHub repository has 3,112 stars, 674 forks, and 99 contributors. It is actively developed with 131 commits in the last 12 months. The latest release, v7.0.4, was published on Sep 6, 2026. On npm it is downloaded about 135.6K times per week. ### Alternatives - [react-native-maps](https://awesomedataviz.com/tools/react-native-maps/): Map view component for iOS and Android in React Native. (16K stars) - [F2](https://awesomedataviz.com/tools/f2/): An elegant, interactive and flexible charting library for mobile, maintained by Alibaba (8K stars) - [react-native-graph](https://awesomedataviz.com/tools/react-native-graph/): Animated, high-performance line graphs for React Native, built with Skia. (2.6K stars) - [Victory Native](https://awesomedataviz.com/tools/victory-native/): High-performance charting library for React Native, built on React Native Skia. (1.2K stars) ### Comparisons - [React Native Chart Kit vs react-native-maps](https://awesomedataviz.com/compare/react-native-chart-kit-vs-react-native-maps/) - [F2 vs React Native Chart Kit](https://awesomedataviz.com/compare/f2-vs-react-native-chart-kit/) - [React Native Chart Kit vs react-native-graph](https://awesomedataviz.com/compare/react-native-chart-kit-vs-react-native-graph/) - [React Native Chart Kit vs Victory Native](https://awesomedataviz.com/compare/react-native-chart-kit-vs-victory-native/) Source: https://awesomedataviz.com/tools/react-native-chart-kit/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## asciigraph > Lightweight ASCII line graphs for command-line apps. - Category: [Go charting & plotting libraries](https://awesomedataviz.com/categories/go/) - Website: https://pkg.go.dev/github.com/guptarohit/asciigraph - Repository: https://github.com/guptarohit/asciigraph - License: BSD-3-Clause - Language: Go - Status: Maintained (commits in the last 12 months) - GitHub stars: 3,099 - Commits in the last 12 months: 72 - Contributors: 19 - Last commit: Jun 21, 2026 - Latest release: v0.10.0 (Jun 21, 2026) - Install (Go): `go get github.com/guptarohit/asciigraph` - Topics: Terminal & command-line charts ### Overview asciigraph is an open-source Go plotting library released under the BSD-3-Clause license. Its GitHub repository has 3,099 stars, 123 forks, and 19 contributors. It is maintained with 72 commits in the last 12 months; the most recent commit was on Jun 21, 2026. The latest release, v0.10.0, was published on Jun 21, 2026. ### Alternatives - [termui](https://awesomedataviz.com/tools/termui/): Terminal dashboard and widget library with charts, gauges, sparklines and more. (13.6K stars) - [go-echarts](https://awesomedataviz.com/tools/go-echarts/): Simple yet powerful data visualizing library for Go. (7.6K stars) - [go-diagrams](https://awesomedataviz.com/tools/go-diagrams/): Diagram-as-code library for system architecture diagrams in Go, rendered with Graphviz. (5.2K stars) - [termdash](https://awesomedataviz.com/tools/termdash/): Terminal-based dashboard library with line charts, bar charts, gauges and donuts. (3K stars) - [plot](https://awesomedataviz.com/tools/plot/): API for building and drawing plots in Go. (3K stars) - [svgo](https://awesomedataviz.com/tools/svgo/): Go Language Library for SVG generation. (2.3K stars) ### Comparisons - [asciigraph vs termui](https://awesomedataviz.com/compare/asciigraph-vs-termui/) - [asciigraph vs go-echarts](https://awesomedataviz.com/compare/asciigraph-vs-go-echarts/) - [asciigraph vs go-diagrams](https://awesomedataviz.com/compare/asciigraph-vs-go-diagrams/) - [asciigraph vs termdash](https://awesomedataviz.com/compare/asciigraph-vs-termdash/) Source: https://awesomedataviz.com/tools/asciigraph/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## termdash > Terminal-based dashboard library with line charts, bar charts, gauges and donuts. - Category: [Go charting & plotting libraries](https://awesomedataviz.com/categories/go/) - Repository: https://github.com/mum4k/termdash - License: Apache-2.0 - Language: Go - Status: Maintained (commits in the last 12 months) - GitHub stars: 3,041 - Commits in the last 12 months: 21 - Contributors: 19 - Last commit: Jun 9, 2026 - Latest release: v0.20.0 (Mar 10, 2024) - Install (Go): `go get github.com/mum4k/termdash` - Topics: Terminal & command-line charts, Dashboards & BI ### Overview termdash is an open-source Go plotting library released under the Apache-2.0 license. Its GitHub repository has 3,041 stars, 150 forks, and 19 contributors. It is maintained with 21 commits in the last 12 months; the most recent commit was on Jun 9, 2026. The latest release, v0.20.0, was published on Mar 10, 2024. ### Alternatives - [termui](https://awesomedataviz.com/tools/termui/): Terminal dashboard and widget library with charts, gauges, sparklines and more. (13.6K stars) - [go-echarts](https://awesomedataviz.com/tools/go-echarts/): Simple yet powerful data visualizing library for Go. (7.6K stars) - [go-diagrams](https://awesomedataviz.com/tools/go-diagrams/): Diagram-as-code library for system architecture diagrams in Go, rendered with Graphviz. (5.2K stars) - [asciigraph](https://awesomedataviz.com/tools/asciigraph/): Lightweight ASCII line graphs for command-line apps. (3.1K stars) - [plot](https://awesomedataviz.com/tools/plot/): API for building and drawing plots in Go. (3K stars) - [svgo](https://awesomedataviz.com/tools/svgo/): Go Language Library for SVG generation. (2.3K stars) ### Comparisons - [termdash vs termui](https://awesomedataviz.com/compare/termdash-vs-termui/) - [go-echarts vs termdash](https://awesomedataviz.com/compare/go-echarts-vs-termdash/) - [go-diagrams vs termdash](https://awesomedataviz.com/compare/go-diagrams-vs-termdash/) - [asciigraph vs termdash](https://awesomedataviz.com/compare/asciigraph-vs-termdash/) Source: https://awesomedataviz.com/tools/termdash/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## flutter_map > Vendor-free, customizable interactive map package for Flutter. - Category: [Flutter chart libraries](https://awesomedataviz.com/categories/flutter/) - Website: https://pub.dev/packages/flutter_map - Repository: https://github.com/fleaflet/flutter_map - License: BSD-3-Clause - Language: Dart - Status: Active (commits in the last 90 days) - GitHub stars: 3,023 - Commits in the last 12 months: 42 - Contributors: 165 - Last commit: Sep 4, 2026 - Latest release: v8.3.2 (Aug 27, 2026) - Install (pub.dev): `flutter pub add flutter_map`, 869K downloads per 30 days - Topics: Maps & geospatial visualization ### Overview flutter_map is an open-source Flutter chart library released under the BSD-3-Clause license. Its GitHub repository has 3,023 stars, 918 forks, and 165 contributors. It is actively developed with 42 commits in the last 12 months. The latest release, v8.3.2, was published on Aug 27, 2026. On pub.dev it is downloaded about 869K times per 30 days. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [react-native-maps](https://awesomedataviz.com/tools/react-native-maps/): Map view component for iOS and Android in React Native. (16K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) ### Comparisons - [fl_chart vs flutter_map](https://awesomedataviz.com/compare/fl-chart-vs-flutter-map/) - [flutter_map vs Graphic](https://awesomedataviz.com/compare/flutter-map-vs-graphic/) Source: https://awesomedataviz.com/tools/flutter-map/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## plot > API for building and drawing plots in Go. - Category: [Go charting & plotting libraries](https://awesomedataviz.com/categories/go/) - Repository: https://github.com/gonum/plot - License: BSD-3-Clause - Language: Go - Status: Maintained (commits in the last 12 months) - GitHub stars: 2,969 - Commits in the last 12 months: 5 - Contributors: 34 - Last commit: Apr 22, 2026 - Latest release: v0.16.0 (Mar 27, 2025) - Install (Go): `go get gonum.org/v1/plot` ### Overview plot is an open-source Go plotting library released under the BSD-3-Clause license. Its GitHub repository has 2,969 stars, 202 forks, and 34 contributors. It is maintained with 5 commits in the last 12 months; the most recent commit was on Apr 22, 2026. The latest release, v0.16.0, was published on Mar 27, 2025. ### Alternatives - [termui](https://awesomedataviz.com/tools/termui/): Terminal dashboard and widget library with charts, gauges, sparklines and more. (13.6K stars) - [go-echarts](https://awesomedataviz.com/tools/go-echarts/): Simple yet powerful data visualizing library for Go. (7.6K stars) - [go-diagrams](https://awesomedataviz.com/tools/go-diagrams/): Diagram-as-code library for system architecture diagrams in Go, rendered with Graphviz. (5.2K stars) - [asciigraph](https://awesomedataviz.com/tools/asciigraph/): Lightweight ASCII line graphs for command-line apps. (3.1K stars) - [termdash](https://awesomedataviz.com/tools/termdash/): Terminal-based dashboard library with line charts, bar charts, gauges and donuts. (3K stars) - [svgo](https://awesomedataviz.com/tools/svgo/): Go Language Library for SVG generation. (2.3K stars) Source: https://awesomedataviz.com/tools/plot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Rill > BI tool for fast, metrics-first dashboards powered by OLAP engines such as DuckDB and ClickHouse. - Category: [Open-source dashboards & BI tools](https://awesomedataviz.com/categories/dashboards-and-bi/) - Website: https://www.rilldata.com - Repository: https://github.com/rilldata/rill - License: Apache-2.0 - Language: Go - Status: Active (commits in the last 90 days) - GitHub stars: 2,928 - Commits in the last 12 months: 1,540 - Contributors: 53 - Last commit: Oct 2, 2026 - Latest release: v0.90.2 (Sep 25, 2026) - Install (Go): `go get github.com/rilldata/rill` - Topics: Dashboards & BI ### Overview Rill is an open-source dashboard and BI tool released under the Apache-2.0 license. Its GitHub repository has 2,928 stars, 202 forks, and 53 contributors. It is actively developed with 1,540 commits in the last 12 months. The latest release, v0.90.2, was published on Sep 25, 2026. ### Alternatives - [Grafana](https://awesomedataviz.com/tools/grafana/): Observability and data visualization platform for metrics, logs and traces from many data sources. (77.1K stars) - [Apache Superset](https://awesomedataviz.com/tools/superset/): Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. (75K stars) - [Metabase](https://awesomedataviz.com/tools/metabase/): Business intelligence tool for querying data and building dashboards, with embedded analytics. (49.5K stars) - [Redash](https://awesomedataviz.com/tools/redash/): Query data sources with SQL, then visualize the results and build dashboards. (28.8K stars) - [Kibana](https://awesomedataviz.com/tools/kibana/): Visualization and dashboard UI for data stored in Elasticsearch. (21.3K stars) - [Evidence](https://awesomedataviz.com/tools/evidence/): Business intelligence as code: build reports and dashboards with SQL and Markdown. (7K stars) Source: https://awesomedataviz.com/tools/rill/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## HoloViews > Complex and declarative visualizations from annotated data. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://holoviews.org/ - Repository: https://github.com/holoviz/holoviews - License: BSD-3-Clause - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 2,910 - Commits in the last 12 months: 321 - Contributors: 150 - Last commit: Oct 2, 2026 - Latest release: v1.23.2 (Aug 24, 2026) - Install (PyPI): `pip install holoviews`, 174.8K downloads per week - Topics: Jupyter & notebook visualization ### Overview HoloViews is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 2,910 stars, 417 forks, and 150 contributors. It is actively developed with 321 commits in the last 12 months. The latest release, v1.23.2, was published on Aug 24, 2026. On PyPI it is downloaded about 174.8K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/holoviews/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Unovis > Modular data visualization framework for React, Angular, Svelte, Vue and vanilla TypeScript, by F5. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://unovis.dev - Repository: https://github.com/f5/unovis - License: Apache-2.0 - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 2,857 - Commits in the last 12 months: 590 - Contributors: 26 - Last commit: Oct 2, 2026 - Latest release: 1.7.1 (Sep 29, 2026) - Install (npm): `npm install @unovis/ts`, 298.6K downloads per week ### Overview Unovis is an open-source JavaScript charting library released under the Apache-2.0 license. Its GitHub repository has 2,857 stars, 72 forks, and 26 contributors. It is actively developed with 590 commits in the last 12 months. The latest release, 1.7.1, was published on Sep 29, 2026. On npm it is downloaded about 298.6K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/unovis/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Makie > Interactive, high-performance plotting ecosystem for Julia with OpenGL, WebGL and Cairo backends. - Category: [Julia plotting packages](https://awesomedataviz.com/categories/julia/) - Website: https://docs.makie.org/stable - Repository: https://github.com/MakieOrg/Makie.jl - License: MIT - Language: Julia - Status: Active (commits in the last 90 days) - GitHub stars: 2,816 - Commits in the last 12 months: 199 - Contributors: 264 - Last commit: Oct 3, 2026 - Latest release: v0.24.15 (Sep 19, 2026) - Install (Julia): `julia -e 'using Pkg; Pkg.add("Makie")'` - Topics: GPU-accelerated & WebGL visualization ### Overview Makie is an open-source Julia plotting package released under the MIT license. Its GitHub repository has 2,816 stars, 396 forks, and 264 contributors. It is actively developed with 199 commits in the last 12 months. The latest release, v0.24.15, was published on Sep 19, 2026. ### Alternatives - [Plots.jl](https://awesomedataviz.com/tools/plots-jl/): Plotting meta-package for Julia with a single API over multiple backends. (2K stars) - [Gadfly.jl](https://awesomedataviz.com/tools/gadfly-jl/): Statistical graphics for Julia based on the grammar of graphics. (1.9K stars) - [UnicodePlots.jl](https://awesomedataviz.com/tools/unicodeplots-jl/): Unicode-based scientific plotting in the terminal for Julia. (1.5K stars) ### Comparisons - [Makie vs Plots.jl](https://awesomedataviz.com/compare/makie-vs-plots-jl/) - [Gadfly.jl vs Makie](https://awesomedataviz.com/compare/gadfly-jl-vs-makie/) - [Makie vs UnicodePlots.jl](https://awesomedataviz.com/compare/makie-vs-unicodeplots-jl/) Source: https://awesomedataviz.com/tools/makie/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## elkjs > Eclipse Layout Kernel (ELK) graph layout algorithms for JavaScript. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Repository: https://github.com/kieler/elkjs - License: EPL-2.0 OR GPL-3.0-or-later - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 2,801 - Commits in the last 12 months: 61 - Contributors: 23 - Last commit: Sep 17, 2026 - Latest release: 0.12.0 (Jul 17, 2026) - Install (npm): `npm install elkjs`, 11.8M downloads per week - Topics: Graph & network visualization ### Overview elkjs is a JavaScript graph visualization library. Its GitHub repository has 2,801 stars, 127 forks, and 23 contributors. It is actively developed with 61 commits in the last 12 months. The latest release, 0.12.0, was published on Jul 17, 2026. On npm it is downloaded about 11.8M times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) Source: https://awesomedataviz.com/tools/elkjs/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## napari > Fast, interactive viewer for multi-dimensional images in Python. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://napari.org - Repository: https://github.com/napari/napari - License: BSD-3-Clause - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 2,771 - Commits in the last 12 months: 641 - Contributors: 220 - Last commit: Oct 3, 2026 - Latest release: v0.9.2 (Sep 29, 2026) - Install (PyPI): `pip install napari`, 27.2K downloads per week ### Overview napari is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 2,771 stars, 548 forks, and 220 contributors. It is actively developed with 641 commits in the last 12 months. The latest release, v0.9.2, was published on Sep 29, 2026. On PyPI it is downloaded about 27.2K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/napari/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Core Plot > 2D plotting framework for macOS, iOS and tvOS. - Category: [iOS & Swift chart libraries](https://awesomedataviz.com/categories/ios/) - Repository: https://github.com/core-plot/core-plot - License: BSD-3-Clause - Language: Objective-C - Status: Inactive (no commits in over a year) - GitHub stars: 2,758 - Commits in the last 12 months: 0 - Contributors: 33 - Last commit: Nov 22, 2023 - Latest release: release_2.3 (Jan 10, 2020) ### Overview Core Plot is an open-source iOS chart library released under the BSD-3-Clause license. Its GitHub repository has 2,758 stars, 594 forks, and 33 contributors. It has not had a commit since Nov 22, 2023. The latest release, release_2.3, was published on Jan 10, 2020. ### Alternatives - [Charts](https://awesomedataviz.com/tools/charts/): IOS port of MPAndroidChart. You can create charts for both platforms with very similar code. (28K stars) - [PNChart](https://awesomedataviz.com/tools/pnchart/): A simple and beautiful chart lib used in Piner and CoinsMan. (9.6K stars) - [ChartView](https://awesomedataviz.com/tools/chartview/): Line, bar and pie chart views built with SwiftUI. (5.6K stars) - [JBChartView](https://awesomedataviz.com/tools/jbchartview/): Charting library for both line and bar graphs. (3.7K stars) - [BEMSimpleLineGraph](https://awesomedataviz.com/tools/bemsimplelinegraph/): Highly customizable and interactive line graphs. (2.6K stars) - [SwiftCharts](https://awesomedataviz.com/tools/swiftcharts/): Customizable charts library for iOS. (2.6K stars) ### Comparisons - [Charts vs Core Plot](https://awesomedataviz.com/compare/charts-vs-core-plot/) - [Core Plot vs PNChart](https://awesomedataviz.com/compare/core-plot-vs-pnchart/) - [ChartView vs Core Plot](https://awesomedataviz.com/compare/chartview-vs-core-plot/) - [Core Plot vs JBChartView](https://awesomedataviz.com/compare/core-plot-vs-jbchartview/) Source: https://awesomedataviz.com/tools/core-plot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Charted > A charting tool that produces automatic, shareable charts from any data file. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: http://charted.co - Repository: https://github.com/charted-co/charted - License: MIT - Language: JavaScript - Status: Archived (the repository is archived and read-only) - GitHub stars: 2,745 - Commits in the last 12 months: 0 - Contributors: 11 - Last commit: Oct 15, 2017 - Latest release: 0.2.4 (Sep 15, 2015) ### Overview Charted is an open-source data visualization app released under the MIT license. Its GitHub repository has 2,745 stars, 182 forks, and 11 contributors. Its repository is archived on GitHub and no longer receives updates. The latest release, 0.2.4, was published on Sep 15, 2015. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/charted/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Semiotic > React data visualization library for charts, network graphs and streaming data. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://semiotic.nteract.io - Repository: https://github.com/nteract/semiotic - License: Apache-2.0 - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 2,710 - Commits in the last 12 months: 2,547 - Contributors: 31 - Last commit: Oct 3, 2026 - Latest release: v3.12.0 (Oct 1, 2026) - Install (npm): `npm install semiotic`, 16.9K downloads per week - Topics: Graph & network visualization, Time series & real-time charts ### Overview Semiotic is an open-source React chart library released under the Apache-2.0 license. Its GitHub repository has 2,710 stars, 140 forks, and 31 contributors. It is actively developed with 2,547 commits in the last 12 months. The latest release, v3.12.0, was published on Oct 1, 2026. On npm it is downloaded about 16.9K times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) Source: https://awesomedataviz.com/tools/semiotic/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## plotly (R) > Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://plotly-r.com - Repository: https://github.com/plotly/plotly.R - License: MIT - Language: R - Status: Active (commits in the last 90 days) - GitHub stars: 2,682 - Commits in the last 12 months: 19 - Contributors: 57 - Last commit: Jul 25, 2026 - Latest release: v4.12.1 (Jul 25, 2026) - Install (CRAN): `install.packages("plotly")`, 59.9K downloads per week ### Overview plotly (R) is an open-source R visualization package released under the MIT license. Its GitHub repository has 2,682 stars, 640 forks, and 57 contributors. It is actively developed with 19 commits in the last 12 months. The latest release, v4.12.1, was published on Jul 25, 2026. On CRAN it is downloaded about 59.9K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) - [gt](https://awesomedataviz.com/tools/gt/): Builds publication-quality display tables in R. (2.2K stars) ### Comparisons - [ggplot2 vs plotly (R)](https://awesomedataviz.com/compare/ggplot2-vs-plotly-r/) - [plotly (R) vs Shiny](https://awesomedataviz.com/compare/plotly-r-vs-shiny/) - [patchwork vs plotly (R)](https://awesomedataviz.com/compare/patchwork-vs-plotly-r/) - [ggstatsplot vs plotly (R)](https://awesomedataviz.com/compare/ggstatsplot-vs-plotly-r/) Source: https://awesomedataviz.com/tools/plotly-r/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Uber React Digraph > React.js based directed graph library maintained by UBER. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Repository: https://github.com/uber/react-digraph - License: MIT - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 2,644 - Commits in the last 12 months: 0 - Contributors: 44 - Last commit: Sep 5, 2023 - Latest release: v8.1.0 (Sep 27, 2022) - Install (npm): `npm install react-digraph`, 3.2K downloads per week - Topics: Graph & network visualization ### Overview Uber React Digraph is an open-source JavaScript graph visualization library released under the MIT license. Its GitHub repository has 2,644 stars, 263 forks, and 44 contributors. It has not had a commit since Sep 5, 2023. The latest release, v8.1.0, was published on Sep 27, 2022. On npm it is downloaded about 3.2K times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) Source: https://awesomedataviz.com/tools/uber-react-digraph/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## BEMSimpleLineGraph > Highly customizable and interactive line graphs. - Category: [iOS & Swift chart libraries](https://awesomedataviz.com/categories/ios/) - Repository: https://github.com/Boris-Em/BEMSimpleLineGraph - License: MIT - Language: Objective-C - Status: Archived (the repository is archived and read-only) - GitHub stars: 2,627 - Commits in the last 12 months: 0 - Contributors: 16 - Last commit: May 1, 2019 - Latest release: v4.1.1 (Jan 24, 2016) ### Overview BEMSimpleLineGraph is an open-source iOS chart library released under the MIT license. Its GitHub repository has 2,627 stars, 369 forks, and 16 contributors. Its repository is archived on GitHub and no longer receives updates. The latest release, v4.1.1, was published on Jan 24, 2016. ### Alternatives - [Charts](https://awesomedataviz.com/tools/charts/): IOS port of MPAndroidChart. You can create charts for both platforms with very similar code. (28K stars) - [PNChart](https://awesomedataviz.com/tools/pnchart/): A simple and beautiful chart lib used in Piner and CoinsMan. (9.6K stars) - [ChartView](https://awesomedataviz.com/tools/chartview/): Line, bar and pie chart views built with SwiftUI. (5.6K stars) - [JBChartView](https://awesomedataviz.com/tools/jbchartview/): Charting library for both line and bar graphs. (3.7K stars) - [Core Plot](https://awesomedataviz.com/tools/core-plot/): 2D plotting framework for macOS, iOS and tvOS. (2.8K stars) - [SwiftCharts](https://awesomedataviz.com/tools/swiftcharts/): Customizable charts library for iOS. (2.6K stars) Source: https://awesomedataviz.com/tools/bemsimplelinegraph/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## react-native-graph > Animated, high-performance line graphs for React Native, built with Skia. - Category: [React Native chart libraries](https://awesomedataviz.com/categories/react-native/) - Website: https://margelo.com - Repository: https://github.com/margelo/react-native-graph - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 2,627 - Commits in the last 12 months: 20 - Contributors: 17 - Last commit: Sep 17, 2026 - Latest release: v1.4.0 (Aug 24, 2026) - Install (npm): `npm install react-native-graph`, 22.5K downloads per week ### Overview react-native-graph is an open-source React Native chart library released under the MIT license. Its GitHub repository has 2,627 stars, 137 forks, and 17 contributors. It is actively developed with 20 commits in the last 12 months. The latest release, v1.4.0, was published on Aug 24, 2026. On npm it is downloaded about 22.5K times per week. ### Alternatives - [react-native-maps](https://awesomedataviz.com/tools/react-native-maps/): Map view component for iOS and Android in React Native. (16K stars) - [F2](https://awesomedataviz.com/tools/f2/): An elegant, interactive and flexible charting library for mobile, maintained by Alibaba (8K stars) - [React Native Chart Kit](https://awesomedataviz.com/tools/react-native-chart-kit/): Line, bar, pie, progress and contribution graph charts for React Native. (3.1K stars) - [Victory Native](https://awesomedataviz.com/tools/victory-native/): High-performance charting library for React Native, built on React Native Skia. (1.2K stars) ### Comparisons - [react-native-graph vs react-native-maps](https://awesomedataviz.com/compare/react-native-graph-vs-react-native-maps/) - [F2 vs react-native-graph](https://awesomedataviz.com/compare/f2-vs-react-native-graph/) - [React Native Chart Kit vs react-native-graph](https://awesomedataviz.com/compare/react-native-chart-kit-vs-react-native-graph/) - [react-native-graph vs Victory Native](https://awesomedataviz.com/compare/react-native-graph-vs-victory-native/) Source: https://awesomedataviz.com/tools/react-native-graph/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## patchwork > Composes multiple ggplot2 plots into a single figure. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://patchwork.data-imaginist.com - Repository: https://github.com/thomasp85/patchwork - License: MIT - Language: R - Status: Inactive (no commits in over a year) - GitHub stars: 2,615 - Commits in the last 12 months: 0 - Contributors: 17 - Last commit: Aug 25, 2025 - Latest release: v1.3.2 (Aug 25, 2025) - Install (CRAN): `install.packages("patchwork")`, 74.8K downloads per week - Topics: Grammar of graphics libraries ### Overview patchwork is an open-source R visualization package released under the MIT license. Its GitHub repository has 2,615 stars, 171 forks, and 17 contributors. It has not had a commit since Aug 25, 2025. The latest release, v1.3.2, was published on Aug 25, 2025. On CRAN it is downloaded about 74.8K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) - [gt](https://awesomedataviz.com/tools/gt/): Builds publication-quality display tables in R. (2.2K stars) ### Comparisons - [ggplot2 vs patchwork](https://awesomedataviz.com/compare/ggplot2-vs-patchwork/) - [patchwork vs Shiny](https://awesomedataviz.com/compare/patchwork-vs-shiny/) - [patchwork vs plotly (R)](https://awesomedataviz.com/compare/patchwork-vs-plotly-r/) - [ggstatsplot vs patchwork](https://awesomedataviz.com/compare/ggstatsplot-vs-patchwork/) Source: https://awesomedataviz.com/tools/patchwork/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Charming > Chart rendering library for Rust powered by Apache ECharts. - Category: [Rust plotting & visualization libraries](https://awesomedataviz.com/categories/rust/) - Repository: https://github.com/yuankunzhang/charming - License: Apache-2.0 - Language: Rust - Status: Active (commits in the last 90 days) - GitHub stars: 2,600 - Commits in the last 12 months: 12 - Contributors: 25 - Last commit: Sep 27, 2026 - Install (crates.io): `cargo add charming`, 292.1K downloads per 90 days ### Overview Charming is an open-source Rust visualization library released under the Apache-2.0 license. Its GitHub repository has 2,600 stars, 119 forks, and 25 contributors. It is actively developed with 12 commits in the last 12 months. On crates.io it is downloaded about 292.1K times per 90 days. ### Alternatives - [Plotters](https://awesomedataviz.com/tools/plotters/): Drawing library for data plotting in Rust, with bitmap, SVG, WebAssembly and GUI backends. (4.6K stars) - [Plotly.rs](https://awesomedataviz.com/tools/plotly-rs/): Plotly.js-based interactive plotting library for Rust. (1.5K stars) - [malevich](https://awesomedataviz.com/tools/malevich/): Terminal plotting: line, scatter, bar, histogram, heatmap, box plot, violin and more, with automatic axes. (70 stars) ### Comparisons - [Charming vs Plotters](https://awesomedataviz.com/compare/charming-vs-plotters/) - [Charming vs Plotly.rs](https://awesomedataviz.com/compare/charming-vs-plotly-rs/) - [Charming vs malevich](https://awesomedataviz.com/compare/charming-vs-malevich/) Source: https://awesomedataviz.com/tools/charming/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## SwiftCharts > Customizable charts library for iOS. - Category: [iOS & Swift chart libraries](https://awesomedataviz.com/categories/ios/) - Repository: https://github.com/ivnsch/SwiftCharts - License: Apache-2.0 - Language: Swift - Status: Inactive (no commits in over a year) - GitHub stars: 2,572 - Commits in the last 12 months: 0 - Contributors: 32 - Last commit: Aug 18, 2022 ### Overview SwiftCharts is an open-source iOS chart library released under the Apache-2.0 license. Its GitHub repository has 2,572 stars, 403 forks, and 32 contributors. It has not had a commit since Aug 18, 2022. ### Alternatives - [Charts](https://awesomedataviz.com/tools/charts/): IOS port of MPAndroidChart. You can create charts for both platforms with very similar code. (28K stars) - [PNChart](https://awesomedataviz.com/tools/pnchart/): A simple and beautiful chart lib used in Piner and CoinsMan. (9.6K stars) - [ChartView](https://awesomedataviz.com/tools/chartview/): Line, bar and pie chart views built with SwiftUI. (5.6K stars) - [JBChartView](https://awesomedataviz.com/tools/jbchartview/): Charting library for both line and bar graphs. (3.7K stars) - [Core Plot](https://awesomedataviz.com/tools/core-plot/): 2D plotting framework for macOS, iOS and tvOS. (2.8K stars) - [BEMSimpleLineGraph](https://awesomedataviz.com/tools/bemsimplelinegraph/): Highly customizable and interactive line graphs. (2.6K stars) Source: https://awesomedataviz.com/tools/swiftcharts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Perses > CNCF dashboard tool and open dashboard specification for observability data such as Prometheus metrics. - Category: [Open-source dashboards & BI tools](https://awesomedataviz.com/categories/dashboards-and-bi/) - Website: https://perses.dev - Repository: https://github.com/perses/perses - License: Apache-2.0 - Language: Go - Status: Active (commits in the last 90 days) - GitHub stars: 2,468 - Commits in the last 12 months: 592 - Contributors: 106 - Last commit: Oct 2, 2026 - Latest release: v0.54.0 (Jul 29, 2026) - Install (Go): `go get github.com/perses/perses` - Topics: Dashboards & BI ### Overview Perses is an open-source dashboard and BI tool released under the Apache-2.0 license. Its GitHub repository has 2,468 stars, 255 forks, and 106 contributors. It is actively developed with 592 commits in the last 12 months. The latest release, v0.54.0, was published on Jul 29, 2026. ### Alternatives - [Grafana](https://awesomedataviz.com/tools/grafana/): Observability and data visualization platform for metrics, logs and traces from many data sources. (77.1K stars) - [Apache Superset](https://awesomedataviz.com/tools/superset/): Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. (75K stars) - [Metabase](https://awesomedataviz.com/tools/metabase/): Business intelligence tool for querying data and building dashboards, with embedded analytics. (49.5K stars) - [Redash](https://awesomedataviz.com/tools/redash/): Query data sources with SQL, then visualize the results and build dashboards. (28.8K stars) - [Kibana](https://awesomedataviz.com/tools/kibana/): Visualization and dashboard UI for data stored in Elasticsearch. (21.3K stars) - [Evidence](https://awesomedataviz.com/tools/evidence/): Business intelligence as code: build reports and dashboards with SQL and Markdown. (7K stars) Source: https://awesomedataviz.com/tools/perses/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## TechanJS > Stock and financial charts. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://techanjs.org/ - Repository: https://github.com/andredumas/techan.js - License: MIT - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 2,436 - Commits in the last 12 months: 0 - Contributors: 7 - Last commit: Oct 10, 2016 - Latest release: 0.8.0 (Oct 1, 2016) - Install (npm): `npm install techan`, 87 downloads per week - Topics: Financial & stock charts ### Overview TechanJS is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 2,436 stars, 522 forks, and 7 contributors. It has not had a commit since Oct 10, 2016. The latest release, 0.8.0, was published on Oct 1, 2016. On npm it is downloaded about 87 times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/techanjs/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Piecon > Pie charts in your favicon. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Repository: https://github.com/lipka/piecon - License: MIT - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 2,295 - Commits in the last 12 months: 0 - Contributors: 4 - Last commit: Oct 12, 2022 - Latest release: 0.5.0 (Nov 19, 2015) - Install (npm): `npm install piecon`, 212 downloads per week ### Overview Piecon is an open-source JavaScript visualization library released under the MIT license. Its GitHub repository has 2,295 stars, 114 forks, and 4 contributors. It has not had a commit since Oct 12, 2022. The latest release, 0.5.0, was published on Nov 19, 2015. On npm it is downloaded about 212 times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) Source: https://awesomedataviz.com/tools/piecon/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## vedo > Library for scientific analysis and visualization of 3D objects based on VTK. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://vedo.embl.es - Repository: https://github.com/marcomusy/vedo - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 2,272 - Commits in the last 12 months: 263 - Contributors: 38 - Last commit: Aug 4, 2026 - Latest release: v2026.6.1 (Feb 17, 2026) - Install (PyPI): `pip install vedo`, 8.2K downloads per week - Topics: 3D & scientific visualization ### Overview vedo is an open-source Python visualization library released under the MIT license. Its GitHub repository has 2,272 stars, 276 forks, and 38 contributors. It is actively developed with 263 commits in the last 12 months. The latest release, v2026.6.1, was published on Feb 17, 2026. On PyPI it is downloaded about 8.2K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/vedo/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## MapLibre Native > Interactive vector tile map rendering for iOS, Android and other native platforms. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Website: https://maplibre.org - Repository: https://github.com/maplibre/maplibre-native - License: BSD-2-Clause - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 2,251 - Commits in the last 12 months: 414 - Contributors: 354 - Last commit: Oct 4, 2026 - Latest release: android-v13.5.2 (Sep 23, 2026) - Topics: Maps & geospatial visualization ### Overview MapLibre Native is an open-source C++ visualization tool released under the BSD-2-Clause license. Its GitHub repository has 2,251 stars, 632 forks, and 354 contributors. It is actively developed with 414 commits in the last 12 months. The latest release, android-v13.5.2, was published on Sep 23, 2026. ### Alternatives - [ImPlot](https://awesomedataviz.com/tools/implot/): Immediate-mode plotting library for Dear ImGui. (6.2K stars) - [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/): Open-source Qt5 application to plot charts (based on Qwt). (6.2K stars) - [Matplot++](https://awesomedataviz.com/tools/matplotpp/): C++ graphics library for data visualization with a MATLAB-like API. (4.9K stars) - [F3D](https://awesomedataviz.com/tools/f3d/): Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. (4.7K stars) - [Mapnik](https://awesomedataviz.com/tools/mapnik/): Toolkit for rendering maps, widely used to render OpenStreetMap tiles. (4K stars) - [ROOT](https://awesomedataviz.com/tools/root/): CERN framework for analyzing, storing and visualizing large scientific datasets. (3.3K stars) Source: https://awesomedataviz.com/tools/maplibre-native/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## svgo > Go Language Library for SVG generation. - Category: [Go charting & plotting libraries](https://awesomedataviz.com/categories/go/) - Repository: https://github.com/ajstarks/svgo - License: Other - Language: Go - Status: Inactive (no commits in over a year) - GitHub stars: 2,251 - Commits in the last 12 months: 0 - Contributors: 2 - Last commit: Oct 24, 2021 - Install (Go): `go get github.com/ajstarks/svgo` ### Overview svgo is a Go plotting library. Its GitHub repository has 2,251 stars, 171 forks, and 2 contributors. It has not had a commit since Oct 24, 2021. ### Alternatives - [termui](https://awesomedataviz.com/tools/termui/): Terminal dashboard and widget library with charts, gauges, sparklines and more. (13.6K stars) - [go-echarts](https://awesomedataviz.com/tools/go-echarts/): Simple yet powerful data visualizing library for Go. (7.6K stars) - [go-diagrams](https://awesomedataviz.com/tools/go-diagrams/): Diagram-as-code library for system architecture diagrams in Go, rendered with Graphviz. (5.2K stars) - [asciigraph](https://awesomedataviz.com/tools/asciigraph/): Lightweight ASCII line graphs for command-line apps. (3.1K stars) - [termdash](https://awesomedataviz.com/tools/termdash/): Terminal-based dashboard library with line charts, bar charts, gauges and donuts. (3K stars) - [plot](https://awesomedataviz.com/tools/plot/): API for building and drawing plots in Go. (3K stars) Source: https://awesomedataviz.com/tools/svgo/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Polyscope > Viewer and user interface for 3D geometry processing. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Website: https://polyscope.run - Repository: https://github.com/nmwsharp/polyscope - License: MIT - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 2,214 - Commits in the last 12 months: 61 - Contributors: 31 - Last commit: Sep 6, 2026 - Latest release: v2.6.1 (Feb 26, 2026) - Install (PyPI): `pip install polyscope`, 21.2K downloads per week - Topics: 3D & scientific visualization ### Overview Polyscope is an open-source C++ visualization tool released under the MIT license. Its GitHub repository has 2,214 stars, 242 forks, and 31 contributors. It is actively developed with 61 commits in the last 12 months. The latest release, v2.6.1, was published on Feb 26, 2026. On PyPI it is downloaded about 21.2K times per week. ### Alternatives - [ImPlot](https://awesomedataviz.com/tools/implot/): Immediate-mode plotting library for Dear ImGui. (6.2K stars) - [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/): Open-source Qt5 application to plot charts (based on Qwt). (6.2K stars) - [Matplot++](https://awesomedataviz.com/tools/matplotpp/): C++ graphics library for data visualization with a MATLAB-like API. (4.9K stars) - [F3D](https://awesomedataviz.com/tools/f3d/): Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. (4.7K stars) - [Mapnik](https://awesomedataviz.com/tools/mapnik/): Toolkit for rendering maps, widely used to render OpenStreetMap tiles. (4K stars) - [ROOT](https://awesomedataviz.com/tools/root/): CERN framework for analyzing, storing and visualizing large scientific datasets. (3.3K stars) Source: https://awesomedataviz.com/tools/polyscope/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ggstatsplot > Ggplot2-based plots with statistical test details included in the graphic. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://www.indrapatil.com/ggstatsplot/ - Repository: https://github.com/IndrajeetPatil/ggstatsplot - License: MIT - Language: R - Status: Active (commits in the last 90 days) - GitHub stars: 2,207 - Commits in the last 12 months: 84 - Contributors: 11 - Last commit: Oct 3, 2026 - Latest release: v1.1.1 (Aug 25, 2026) - Install (CRAN): `install.packages("ggstatsplot")`, 1.3K downloads per week - Topics: Grammar of graphics libraries ### Overview ggstatsplot is an open-source R visualization package released under the MIT license. Its GitHub repository has 2,207 stars, 200 forks, and 11 contributors. It is actively developed with 84 commits in the last 12 months. The latest release, v1.1.1, was published on Aug 25, 2026. On CRAN it is downloaded about 1.3K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) - [gt](https://awesomedataviz.com/tools/gt/): Builds publication-quality display tables in R. (2.2K stars) ### Comparisons - [ggplot2 vs ggstatsplot](https://awesomedataviz.com/compare/ggplot2-vs-ggstatsplot/) - [ggstatsplot vs Shiny](https://awesomedataviz.com/compare/ggstatsplot-vs-shiny/) - [ggstatsplot vs plotly (R)](https://awesomedataviz.com/compare/ggstatsplot-vs-plotly-r/) - [ggstatsplot vs patchwork](https://awesomedataviz.com/compare/ggstatsplot-vs-patchwork/) Source: https://awesomedataviz.com/tools/ggstatsplot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Plotext > Plots data directly in the terminal with a matplotlib-like syntax. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://plotext.readthedocs.io - Repository: https://github.com/piccolomo/plotext - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 2,204 - Commits in the last 12 months: 27 - Contributors: 7 - Last commit: Sep 7, 2026 - Latest release: 6.1.0 (Sep 7, 2026) - Install (PyPI): `pip install plotext`, 297.8K downloads per week - Topics: Terminal & command-line charts ### Overview Plotext is an open-source Python visualization library released under the MIT license. Its GitHub repository has 2,204 stars, 91 forks, and 7 contributors. It is actively developed with 27 commits in the last 12 months. The latest release, 6.1.0, was published on Sep 7, 2026. On PyPI it is downloaded about 297.8K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/plotext/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## rayshader > 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://www.rayshader.com/ - Repository: https://github.com/tylermorganwall/rayshader - License: GPL-3.0 - Language: R - Status: Active (commits in the last 90 days) - GitHub stars: 2,182 - Commits in the last 12 months: 33 - Contributors: 8 - Last commit: Jul 20, 2026 - Install (CRAN): `install.packages("rayshader")`, 530 downloads per week - Topics: 3D & scientific visualization, Grammar of graphics libraries ### Overview rayshader is an open-source R visualization package released under the GPL-3.0 license. Its GitHub repository has 2,182 stars, 219 forks, and 8 contributors. It is actively developed with 33 commits in the last 12 months. On CRAN it is downloaded about 530 times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [gt](https://awesomedataviz.com/tools/gt/): Builds publication-quality display tables in R. (2.2K stars) Source: https://awesomedataviz.com/tools/rayshader/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## gt > Builds publication-quality display tables in R. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://gt.rstudio.com - Repository: https://github.com/rstudio/gt - License: MIT - Language: R - Status: Active (commits in the last 90 days) - GitHub stars: 2,161 - Commits in the last 12 months: 939 - Contributors: 57 - Last commit: Sep 14, 2026 - Latest release: v1.3.0 (Jan 22, 2026) - Install (CRAN): `install.packages("gt")`, 31.1K downloads per week ### Overview gt is an open-source R visualization package released under the MIT license. Its GitHub repository has 2,161 stars, 226 forks, and 57 contributors. It is actively developed with 939 commits in the last 12 months. The latest release, v1.3.0, was published on Jan 22, 2026. On CRAN it is downloaded about 31.1K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/gt/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## OpenSearch Dashboards > Visualization and dashboard UI for OpenSearch; Apache-2.0 fork of Kibana 7.10. - Category: [Open-source dashboards & BI tools](https://awesomedataviz.com/categories/dashboards-and-bi/) - Website: https://opensearch.org/docs/latest/dashboards/index/ - Repository: https://github.com/opensearch-project/OpenSearch-Dashboards - License: Apache-2.0 - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 2,130 - Commits in the last 12 months: 941 - Contributors: 348 - Last commit: Oct 3, 2026 - Latest release: 3.8.0 (Sep 1, 2026) - Topics: Dashboards & BI ### Overview OpenSearch Dashboards is an open-source dashboard and BI tool released under the Apache-2.0 license. Its GitHub repository has 2,130 stars, 1,285 forks, and 348 contributors. It is actively developed with 941 commits in the last 12 months. The latest release, 3.8.0, was published on Sep 1, 2026. ### Alternatives - [Grafana](https://awesomedataviz.com/tools/grafana/): Observability and data visualization platform for metrics, logs and traces from many data sources. (77.1K stars) - [Apache Superset](https://awesomedataviz.com/tools/superset/): Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. (75K stars) - [Metabase](https://awesomedataviz.com/tools/metabase/): Business intelligence tool for querying data and building dashboards, with embedded analytics. (49.5K stars) - [Redash](https://awesomedataviz.com/tools/redash/): Query data sources with SQL, then visualize the results and build dashboards. (28.8K stars) - [Kibana](https://awesomedataviz.com/tools/kibana/): Visualization and dashboard UI for data stored in Elasticsearch. (21.3K stars) - [Evidence](https://awesomedataviz.com/tools/evidence/): Business intelligence as code: build reports and dashboards with SQL and Markdown. (7K stars) Source: https://awesomedataviz.com/tools/opensearch-dashboards/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Cola.js > A tool to create diagrams using constraint-based optimization techniques. Works with d3 and svg.js. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Website: https://marvl.infotech.monash.edu/webcola/ - Repository: https://github.com/tgdwyer/WebCola - License: MIT - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 2,098 - Commits in the last 12 months: 3 - Contributors: 31 - Last commit: Apr 30, 2026 - Latest release: v3.3.8 (Mar 19, 2018) - Install (npm): `npm install webcola`, 205.7K downloads per week - Topics: Graph & network visualization, Diagrams & diagrams as code ### Overview Cola.js is an open-source JavaScript graph visualization library released under the MIT license. Its GitHub repository has 2,098 stars, 260 forks, and 31 contributors. It is maintained with 3 commits in the last 12 months; the most recent commit was on Apr 30, 2026. The latest release, v3.3.8, was published on Mar 19, 2018. On npm it is downloaded about 205.7K times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) Source: https://awesomedataviz.com/tools/cola-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Microcharts > Simple cross-platform charts for .NET, drawn with SkiaSharp. - Category: [C# & .NET charting libraries](https://awesomedataviz.com/categories/dotnet/) - Repository: https://github.com/microcharts-dotnet/Microcharts - License: MIT - Language: C# - Status: Active (commits in the last 90 days) - GitHub stars: 2,075 - Commits in the last 12 months: 47 - Contributors: 23 - Last commit: Jul 27, 2026 - Latest release: 2.0.0.3 (Jul 21, 2026) - Install (NuGet): `dotnet add package Microcharts`, 1.5M downloads in total ### Overview Microcharts is an open-source .NET charting library released under the MIT license. Its GitHub repository has 2,075 stars, 356 forks, and 23 contributors. It is actively developed with 47 commits in the last 12 months. The latest release, 2.0.0.3, was published on Jul 21, 2026. It has been downloaded about 1.5M times from NuGet. ### Alternatives - [ScottPlot](https://awesomedataviz.com/tools/scottplot/): Interactive plotting library for .NET with WinForms, WPF, Avalonia, Blazor and other controls. (6.8K stars) - [LiveCharts2](https://awesomedataviz.com/tools/livecharts2/): Animated, interactive charts, maps and gauges for .NET UI frameworks. (5.5K stars) - [OxyPlot](https://awesomedataviz.com/tools/oxyplot/): Cross-platform plotting library for .NET. (3.5K stars) - [Mapsui](https://awesomedataviz.com/tools/mapsui/): .NET map component for MAUI, Avalonia, Uno Platform, Blazor, WPF and WinUI. (1.6K stars) - [MSAGL](https://awesomedataviz.com/tools/msagl/): Microsoft Automatic Graph Layout: tools for graph layout and viewing in .NET. (1.5K stars) ### Comparisons - [Microcharts vs ScottPlot](https://awesomedataviz.com/compare/microcharts-vs-scottplot/) - [LiveCharts2 vs Microcharts](https://awesomedataviz.com/compare/livecharts2-vs-microcharts/) - [Microcharts vs OxyPlot](https://awesomedataviz.com/compare/microcharts-vs-oxyplot/) - [Mapsui vs Microcharts](https://awesomedataviz.com/compare/mapsui-vs-microcharts/) Source: https://awesomedataviz.com/tools/microcharts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## DevExtreme React Chart > High-performance plugin-based React chart for Bootstrap and Material Design. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://devexpress.github.io/devextreme-reactive/react/chart/ - Repository: https://github.com/DevExpress/devextreme-reactive - License: Other - Language: TypeScript - Status: Archived (the repository is archived and read-only) - GitHub stars: 2,068 - Commits in the last 12 months: 1 - Contributors: 60 - Last commit: Dec 19, 2025 - Latest release: v4.0.11 (May 5, 2025) - Install (npm): `npm install @devexpress/dx-react-chart`, 7.2K downloads per week ### Overview DevExtreme React Chart is a React chart library. Its GitHub repository has 2,068 stars, 381 forks, and 60 contributors. Its repository is archived on GitHub and no longer receives updates. The latest release, v4.0.11, was published on May 5, 2025. On npm it is downloaded about 7.2K times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) Source: https://awesomedataviz.com/tools/devextreme-react-chart/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Vizzu > Library for animated data visualizations and data stories. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://lib.vizzuhq.com - Repository: https://github.com/vizzuhq/vizzu-lib - License: Apache-2.0 - Language: JavaScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 2,036 - Commits in the last 12 months: 21 - Contributors: 14 - Last commit: Apr 20, 2026 - Latest release: v0.18.0 (Apr 20, 2026) - Install (npm): `npm install vizzu`, 1K downloads per week ### Overview Vizzu is an open-source JavaScript charting library released under the Apache-2.0 license. Its GitHub repository has 2,036 stars, 87 forks, and 14 contributors. It is maintained with 21 commits in the last 12 months; the most recent commit was on Apr 20, 2026. The latest release, v0.18.0, was published on Apr 20, 2026. On npm it is downloaded about 1K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/vizzu/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## gganimate > Grammar of animated graphics that extends ggplot2. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://gganimate.com - Repository: https://github.com/thomasp85/gganimate - License: MIT - Language: R - Status: Inactive (no commits in over a year) - GitHub stars: 1,983 - Commits in the last 12 months: 0 - Contributors: 27 - Last commit: Sep 4, 2025 - Latest release: v1.0.11 (Sep 4, 2025) - Install (CRAN): `install.packages("gganimate")`, 4.1K downloads per week - Topics: Grammar of graphics libraries ### Overview gganimate is an open-source R visualization package released under the MIT license. Its GitHub repository has 1,983 stars, 315 forks, and 27 contributors. It has not had a commit since Sep 4, 2025. The latest release, v1.0.11, was published on Sep 4, 2025. On CRAN it is downloaded about 4.1K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/gganimate/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Plots.jl > Plotting meta-package for Julia with a single API over multiple backends. - Category: [Julia plotting packages](https://awesomedataviz.com/categories/julia/) - Website: https://docs.juliaplots.org - Repository: https://github.com/JuliaPlots/Plots.jl - Language: Julia - Status: Active (commits in the last 90 days) - GitHub stars: 1,952 - Commits in the last 12 months: 89 - Contributors: 244 - Last commit: Oct 3, 2026 - Latest release: Plots-v1.41.7 (Aug 20, 2026) - Install (Julia): `julia -e 'using Pkg; Pkg.add("Plots")'` ### Overview Plots.jl is a Julia plotting package. Its GitHub repository has 1,952 stars, 386 forks, and 244 contributors. It is actively developed with 89 commits in the last 12 months. The latest release, Plots-v1.41.7, was published on Aug 20, 2026. ### Alternatives - [Makie](https://awesomedataviz.com/tools/makie/): Interactive, high-performance plotting ecosystem for Julia with OpenGL, WebGL and Cairo backends. (2.8K stars) - [Gadfly.jl](https://awesomedataviz.com/tools/gadfly-jl/): Statistical graphics for Julia based on the grammar of graphics. (1.9K stars) - [UnicodePlots.jl](https://awesomedataviz.com/tools/unicodeplots-jl/): Unicode-based scientific plotting in the terminal for Julia. (1.5K stars) ### Comparisons - [Makie vs Plots.jl](https://awesomedataviz.com/compare/makie-vs-plots-jl/) - [Gadfly.jl vs Plots.jl](https://awesomedataviz.com/compare/gadfly-jl-vs-plots-jl/) - [Plots.jl vs UnicodePlots.jl](https://awesomedataviz.com/compare/plots-jl-vs-unicodeplots-jl/) Source: https://awesomedataviz.com/tools/plots-jl/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Gadfly.jl > Statistical graphics for Julia based on the grammar of graphics. - Category: [Julia plotting packages](https://awesomedataviz.com/categories/julia/) - Website: http://gadflyjl.org/stable/ - Repository: https://github.com/GiovineItalia/Gadfly.jl - License: Other - Language: Julia - Status: Inactive (no commits in over a year) - GitHub stars: 1,927 - Commits in the last 12 months: 0 - Contributors: 100 - Last commit: Jun 9, 2025 - Latest release: v1.3.4 (Oct 10, 2021) - Install (Julia): `julia -e 'using Pkg; Pkg.add("Gadfly")'` - Topics: Grammar of graphics libraries ### Overview Gadfly.jl is a Julia plotting package. Its GitHub repository has 1,927 stars, 248 forks, and 100 contributors. It has not had a commit since Jun 9, 2025. The latest release, v1.3.4, was published on Oct 10, 2021. ### Alternatives - [Makie](https://awesomedataviz.com/tools/makie/): Interactive, high-performance plotting ecosystem for Julia with OpenGL, WebGL and Cairo backends. (2.8K stars) - [Plots.jl](https://awesomedataviz.com/tools/plots-jl/): Plotting meta-package for Julia with a single API over multiple backends. (2K stars) - [UnicodePlots.jl](https://awesomedataviz.com/tools/unicodeplots-jl/): Unicode-based scientific plotting in the terminal for Julia. (1.5K stars) ### Comparisons - [Gadfly.jl vs Makie](https://awesomedataviz.com/compare/gadfly-jl-vs-makie/) - [Gadfly.jl vs Plots.jl](https://awesomedataviz.com/compare/gadfly-jl-vs-plots-jl/) - [Gadfly.jl vs UnicodePlots.jl](https://awesomedataviz.com/compare/gadfly-jl-vs-unicodeplots-jl/) Source: https://awesomedataviz.com/tools/gadfly-jl/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## diagram.js > Javascript diagram library serving as the basis for camunda's online BPMN modeler. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Repository: https://github.com/bpmn-io/diagram-js - License: MIT - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 1,926 - Commits in the last 12 months: 268 - Contributors: 58 - Last commit: Oct 1, 2026 - Latest release: v15.28.0 (Oct 1, 2026) - Install (npm): `npm install diagram-js`, 392.6K downloads per week - Topics: Graph & network visualization, Diagrams & diagrams as code ### Overview diagram.js is an open-source JavaScript graph visualization library released under the MIT license. Its GitHub repository has 1,926 stars, 450 forks, and 58 contributors. It is actively developed with 268 commits in the last 12 months. The latest release, v15.28.0, was published on Oct 1, 2026. On npm it is downloaded about 392.6K times per week. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) Source: https://awesomedataviz.com/tools/diagram-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## esquisse > Drag-and-drop interface for building ggplot2 charts in RStudio or Shiny. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://dreamrs.github.io/esquisse - Repository: https://github.com/dreamRs/esquisse - License: GPL-3.0 - Language: R - Status: Inactive (no commits in over a year) - GitHub stars: 1,865 - Commits in the last 12 months: 0 - Contributors: 24 - Last commit: Feb 21, 2025 - Latest release: v2.1.0 (Feb 21, 2025) - Install (CRAN): `install.packages("esquisse")`, 1.3K downloads per week - Topics: Grammar of graphics libraries ### Overview esquisse is an open-source R visualization package released under the GPL-3.0 license. Its GitHub repository has 1,865 stars, 242 forks, and 24 contributors. It has not had a commit since Feb 21, 2025. The latest release, v2.1.0, was published on Feb 21, 2025. On CRAN it is downloaded about 1.3K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/esquisse/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Layer Cake > Graphics framework for building reusable charts with Svelte. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://layercake.graphics - Repository: https://github.com/mhkeller/layercake - License: MIT - Language: Svelte - Status: Active (commits in the last 90 days) - GitHub stars: 1,793 - Commits in the last 12 months: 67 - Contributors: 11 - Last commit: Oct 4, 2026 - Latest release: v11.0.0 (Sep 6, 2026) - Install (npm): `npm install layercake`, 96.2K downloads per week ### Overview Layer Cake is an open-source JavaScript visualization library released under the MIT license. Its GitHub repository has 1,793 stars, 42 forks, and 11 contributors. It is actively developed with 67 commits in the last 12 months. The latest release, v11.0.0, was published on Sep 6, 2026. On npm it is downloaded about 96.2K times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) Source: https://awesomedataviz.com/tools/layer-cake/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Graphic > Grammar of graphics data visualization and charting library for Flutter. - Category: [Flutter chart libraries](https://awesomedataviz.com/categories/flutter/) - Website: https://pub.dev/packages/graphic - Repository: https://github.com/entronad/graphic - License: MIT - Language: Dart - Status: Maintained (commits in the last 12 months) - GitHub stars: 1,792 - Commits in the last 12 months: 7 - Contributors: 19 - Last commit: Feb 25, 2026 - Latest release: v2.7.0 (Feb 25, 2026) - Install (pub.dev): `flutter pub add graphic`, 43.6K downloads per 30 days - Topics: Grammar of graphics libraries ### Overview Graphic is an open-source Flutter chart library released under the MIT license. Its GitHub repository has 1,792 stars, 185 forks, and 19 contributors. It is maintained with 7 commits in the last 12 months; the most recent commit was on Feb 25, 2026. The latest release, v2.7.0, was published on Feb 25, 2026. On pub.dev it is downloaded about 43.6K times per 30 days. ### Alternatives - [G2](https://awesomedataviz.com/tools/g2/): An interactive and responsive charting library based on the grammar of graphics, maintained by Alibaba. (12.6K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Vega-Altair](https://awesomedataviz.com/tools/altair/): Declarative statistical visualizations, based on Vega-Lite. (10.5K stars) - [fl_chart](https://awesomedataviz.com/tools/fl-chart/): Customizable Flutter chart library with line, bar, pie, scatter and radar charts. (7.6K stars) - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [BizCharts](https://awesomedataviz.com/tools/bizcharts/): Data visualization library based on G2 and React. (6.2K stars) ### Comparisons - [fl_chart vs Graphic](https://awesomedataviz.com/compare/fl-chart-vs-graphic/) - [flutter_map vs Graphic](https://awesomedataviz.com/compare/flutter-map-vs-graphic/) Source: https://awesomedataviz.com/tools/graphic/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Lets-Plot > Grammar of graphics plotting library for Python and Kotlin, by JetBrains. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://lets-plot.org - Repository: https://github.com/JetBrains/lets-plot - License: MIT - Language: Kotlin - Status: Maintained (commits in the last 12 months) - GitHub stars: 1,783 - Commits in the last 12 months: 606 - Contributors: 21 - Last commit: Jun 30, 2026 - Latest release: v4.11.0 (Jun 30, 2026) - Install (PyPI): `pip install lets-plot`, 9.2K downloads per week - Topics: Jupyter & notebook visualization, Grammar of graphics libraries ### Overview Lets-Plot is an open-source Python visualization library released under the MIT license. Its GitHub repository has 1,783 stars, 61 forks, and 21 contributors. It is maintained with 606 commits in the last 12 months; the most recent commit was on Jun 30, 2026. The latest release, v4.11.0, was published on Jun 30, 2026. On PyPI it is downloaded about 9.2K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/lets-plot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Graphology > A robust & multipurpose Graph object for javascript & TypeScript; Serves as a base library to power other graph visualization libraries. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://graphology.github.io - Repository: https://github.com/graphology/graphology - License: MIT - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 1,756 - Commits in the last 12 months: 10 - Contributors: 32 - Last commit: Sep 2, 2026 - Latest release: 0.26.0 (Feb 8, 2025) - Install (npm): `npm install graphology`, 1.9M downloads per week - Topics: Graph & network visualization ### Overview Graphology is an open-source JavaScript visualization library released under the MIT license. Its GitHub repository has 1,756 stars, 117 forks, and 32 contributors. It is actively developed with 10 commits in the last 12 months. The latest release, 0.26.0, was published on Feb 8, 2025. On npm it is downloaded about 1.9M times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) Source: https://awesomedataviz.com/tools/graphology/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Shiny for Python > Python version of the Shiny reactive framework for interactive data apps. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://shiny.posit.co/py/ - Repository: https://github.com/posit-dev/py-shiny - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 1,756 - Commits in the last 12 months: 217 - Contributors: 48 - Last commit: Oct 2, 2026 - Latest release: v1.8.0 (Sep 13, 2026) - Install (PyPI): `pip install shiny`, 58K downloads per week ### Overview Shiny for Python is an open-source Python visualization library released under the MIT license. Its GitHub repository has 1,756 stars, 138 forks, and 48 contributors. It is actively developed with 217 commits in the last 12 months. The latest release, v1.8.0, was published on Sep 13, 2026. On PyPI it is downloaded about 58K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) ### Comparisons - [Shiny for Python vs Streamlit](https://awesomedataviz.com/compare/shiny-for-python-vs-streamlit/) Source: https://awesomedataviz.com/tools/shiny-for-python/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## DiagrammeR > Graph and network diagrams in R, rendered with Graphviz and mermaid. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://rich-iannone.github.io/DiagrammeR/ - Repository: https://github.com/rich-iannone/DiagrammeR - License: MIT - Language: R - Status: Maintained (commits in the last 12 months) - GitHub stars: 1,745 - Commits in the last 12 months: 22 - Contributors: 34 - Last commit: Apr 27, 2026 - Latest release: v1.0.12 (Apr 27, 2026) - Install (CRAN): `install.packages("DiagrammeR")`, 11.6K downloads per week - Topics: Graph & network visualization, Diagrams & diagrams as code ### Overview DiagrammeR is an open-source R visualization package released under the MIT license. Its GitHub repository has 1,745 stars, 244 forks, and 34 contributors. It is maintained with 22 commits in the last 12 months; the most recent commit was on Apr 27, 2026. The latest release, v1.0.12, was published on Apr 27, 2026. On CRAN it is downloaded about 11.6K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/diagrammer/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## DataLens > Business intelligence and data visualization system, originally developed at Yandex. - Category: [Open-source dashboards & BI tools](https://awesomedataviz.com/categories/dashboards-and-bi/) - Website: https://datalens.tech/docs - Repository: https://github.com/datalens-tech/datalens - License: Apache-2.0 - Language: PLpgSQL - Status: Active (commits in the last 90 days) - GitHub stars: 1,705 - Commits in the last 12 months: 32 - Contributors: 25 - Last commit: Aug 24, 2026 - Latest release: v2.9.0 (Feb 19, 2026) - Topics: Dashboards & BI ### Overview DataLens is an open-source dashboard and BI tool released under the Apache-2.0 license. Its GitHub repository has 1,705 stars, 120 forks, and 25 contributors. It is actively developed with 32 commits in the last 12 months. The latest release, v2.9.0, was published on Feb 19, 2026. ### Alternatives - [Grafana](https://awesomedataviz.com/tools/grafana/): Observability and data visualization platform for metrics, logs and traces from many data sources. (77.1K stars) - [Apache Superset](https://awesomedataviz.com/tools/superset/): Data exploration and visualization platform with a no-code chart builder, SQL IDE and dashboards. (75K stars) - [Metabase](https://awesomedataviz.com/tools/metabase/): Business intelligence tool for querying data and building dashboards, with embedded analytics. (49.5K stars) - [Redash](https://awesomedataviz.com/tools/redash/): Query data sources with SQL, then visualize the results and build dashboards. (28.8K stars) - [Kibana](https://awesomedataviz.com/tools/kibana/): Visualization and dashboard UI for data stored in Elasticsearch. (21.3K stars) - [Evidence](https://awesomedataviz.com/tools/evidence/): Business intelligence as code: build reports and dashboards with SQL and Markdown. (7K stars) Source: https://awesomedataviz.com/tools/datalens/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ParaView > Multi-platform data analysis and visualization application based on VTK. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Website: http://www.paraview.org - Repository: https://github.com/Kitware/ParaView - License: BSD-3-Clause - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 1,704 - Commits in the last 12 months: 1,916 - Contributors: 216 - Last commit: Oct 4, 2026 ### Overview ParaView is an open-source C++ visualization tool released under the BSD-3-Clause license. Its GitHub repository has 1,704 stars, 494 forks, and 216 contributors. It is actively developed with 1,916 commits in the last 12 months. ### Alternatives - [ImPlot](https://awesomedataviz.com/tools/implot/): Immediate-mode plotting library for Dear ImGui. (6.2K stars) - [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/): Open-source Qt5 application to plot charts (based on Qwt). (6.2K stars) - [Matplot++](https://awesomedataviz.com/tools/matplotpp/): C++ graphics library for data visualization with a MATLAB-like API. (4.9K stars) - [F3D](https://awesomedataviz.com/tools/f3d/): Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. (4.7K stars) - [Mapnik](https://awesomedataviz.com/tools/mapnik/): Toolkit for rendering maps, widely used to render OpenStreetMap tiles. (4K stars) - [ROOT](https://awesomedataviz.com/tools/root/): CERN framework for analyzing, storing and visualizing large scientific datasets. (3.3K stars) Source: https://awesomedataviz.com/tools/paraview/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Cartopy > Cartographic projections and geospatial data plotting with matplotlib. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://cartopy.readthedocs.io/ - Repository: https://github.com/SciTools/cartopy - License: BSD-3-Clause - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 1,621 - Commits in the last 12 months: 212 - Contributors: 127 - Last commit: Sep 24, 2026 - Latest release: v0.26.0 (Sep 17, 2026) - Install (PyPI): `pip install Cartopy`, 197.4K downloads per week - Topics: Maps & geospatial visualization ### Overview Cartopy is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 1,621 stars, 401 forks, and 127 contributors. It is actively developed with 212 commits in the last 12 months. The latest release, v0.26.0, was published on Sep 17, 2026. On PyPI it is downloaded about 197.4K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/cartopy/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## XChart > Lightweight Java library for plotting data. - Category: [Java, Kotlin & Scala visualization libraries](https://awesomedataviz.com/categories/jvm/) - Website: http://knowm.org/open-source/xchart - Repository: https://github.com/knowm/XChart - License: Apache-2.0 - Language: Java - Status: Active (commits in the last 90 days) - GitHub stars: 1,596 - Commits in the last 12 months: 307 - Contributors: 60 - Last commit: Jul 31, 2026 - Install (Maven Central): `implementation("org.knowm.xchart:xchart:3.8.8")` ### Overview XChart is an open-source JVM charting library released under the Apache-2.0 license. Its GitHub repository has 1,596 stars, 398 forks, and 60 contributors. It is actively developed with 307 commits in the last 12 months. ### Alternatives - [JFreeChart](https://awesomedataviz.com/tools/jfreechart/): 2D chart library for Java applications using Swing, JavaFX or server-side rendering. (1.4K stars) - [Kandy](https://awesomedataviz.com/tools/kandy/): Kotlin plotting library with a typed DSL, developed by JetBrains. (746 stars) - [Lets-Plot for Kotlin](https://awesomedataviz.com/tools/lets-plot-for-kotlin/): Grammar of graphics plotting API for Kotlin, built on Lets-Plot. (487 stars) ### Comparisons - [JFreeChart vs XChart](https://awesomedataviz.com/compare/jfreechart-vs-xchart/) - [Kandy vs XChart](https://awesomedataviz.com/compare/kandy-vs-xchart/) - [Lets-Plot for Kotlin vs XChart](https://awesomedataviz.com/compare/lets-plot-for-kotlin-vs-xchart/) Source: https://awesomedataviz.com/tools/xchart/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Mapsui > .NET map component for MAUI, Avalonia, Uno Platform, Blazor, WPF and WinUI. - Category: [C# & .NET charting libraries](https://awesomedataviz.com/categories/dotnet/) - Website: https://mapsui.com - Repository: https://github.com/Mapsui/Mapsui - License: MIT - Language: C# - Status: Active (commits in the last 90 days) - GitHub stars: 1,573 - Commits in the last 12 months: 650 - Contributors: 64 - Last commit: Oct 2, 2026 - Latest release: 5.1.0 (May 27, 2026) - Install (NuGet): `dotnet add package Mapsui`, 1.8M downloads in total - Topics: Maps & geospatial visualization ### Overview Mapsui is an open-source .NET charting library released under the MIT license. Its GitHub repository has 1,573 stars, 357 forks, and 64 contributors. It is actively developed with 650 commits in the last 12 months. The latest release, 5.1.0, was published on May 27, 2026. It has been downloaded about 1.8M times from NuGet. ### Alternatives - [ScottPlot](https://awesomedataviz.com/tools/scottplot/): Interactive plotting library for .NET with WinForms, WPF, Avalonia, Blazor and other controls. (6.8K stars) - [LiveCharts2](https://awesomedataviz.com/tools/livecharts2/): Animated, interactive charts, maps and gauges for .NET UI frameworks. (5.5K stars) - [OxyPlot](https://awesomedataviz.com/tools/oxyplot/): Cross-platform plotting library for .NET. (3.5K stars) - [Microcharts](https://awesomedataviz.com/tools/microcharts/): Simple cross-platform charts for .NET, drawn with SkiaSharp. (2.1K stars) - [MSAGL](https://awesomedataviz.com/tools/msagl/): Microsoft Automatic Graph Layout: tools for graph layout and viewing in .NET. (1.5K stars) ### Comparisons - [Mapsui vs ScottPlot](https://awesomedataviz.com/compare/mapsui-vs-scottplot/) - [LiveCharts2 vs Mapsui](https://awesomedataviz.com/compare/livecharts2-vs-mapsui/) - [Mapsui vs OxyPlot](https://awesomedataviz.com/compare/mapsui-vs-oxyplot/) - [Mapsui vs Microcharts](https://awesomedataviz.com/compare/mapsui-vs-microcharts/) Source: https://awesomedataviz.com/tools/mapsui/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ComplexHeatmap > Highly customizable heatmaps for genomic and other matrix data (Bioconductor). - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://jokergoo.github.io/ComplexHeatmap-reference/book/ - Repository: https://github.com/jokergoo/ComplexHeatmap - License: Other - Language: R - Status: Maintained (commits in the last 12 months) - GitHub stars: 1,557 - Commits in the last 12 months: 3 - Contributors: 20 - Last commit: Apr 2, 2026 - Latest release: 1.99.4 (Dec 12, 2018) ### Overview ComplexHeatmap is an R visualization package. Its GitHub repository has 1,557 stars, 256 forks, and 20 contributors. It is maintained with 3 commits in the last 12 months; the most recent commit was on Apr 2, 2026. The latest release, 1.99.4, was published on Dec 12, 2018. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/complexheatmap/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## UnicodePlots.jl > Unicode-based scientific plotting in the terminal for Julia. - Category: [Julia plotting packages](https://awesomedataviz.com/categories/julia/) - Website: https://juliaplots.org/UnicodePlots.jl - Repository: https://github.com/JuliaPlots/UnicodePlots.jl - License: Other - Language: Julia - Status: Active (commits in the last 90 days) - GitHub stars: 1,549 - Commits in the last 12 months: 31 - Contributors: 45 - Last commit: Oct 3, 2026 - Latest release: UnicodePlots-v3.9.0 (Sep 20, 2026) - Install (Julia): `julia -e 'using Pkg; Pkg.add("UnicodePlots")'` - Topics: Terminal & command-line charts ### Overview UnicodePlots.jl is a Julia plotting package. Its GitHub repository has 1,549 stars, 87 forks, and 45 contributors. It is actively developed with 31 commits in the last 12 months. The latest release, UnicodePlots-v3.9.0, was published on Sep 20, 2026. ### Alternatives - [Makie](https://awesomedataviz.com/tools/makie/): Interactive, high-performance plotting ecosystem for Julia with OpenGL, WebGL and Cairo backends. (2.8K stars) - [Plots.jl](https://awesomedataviz.com/tools/plots-jl/): Plotting meta-package for Julia with a single API over multiple backends. (2K stars) - [Gadfly.jl](https://awesomedataviz.com/tools/gadfly-jl/): Statistical graphics for Julia based on the grammar of graphics. (1.9K stars) ### Comparisons - [Makie vs UnicodePlots.jl](https://awesomedataviz.com/compare/makie-vs-unicodeplots-jl/) - [Plots.jl vs UnicodePlots.jl](https://awesomedataviz.com/compare/plots-jl-vs-unicodeplots-jl/) - [Gadfly.jl vs UnicodePlots.jl](https://awesomedataviz.com/compare/gadfly-jl-vs-unicodeplots-jl/) Source: https://awesomedataviz.com/tools/unicodeplots-jl/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## vtk.js > JavaScript implementation of the Visualization Toolkit (VTK) for scientific visualization on the web. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://kitware.github.io/vtk-js/ - Repository: https://github.com/Kitware/vtk-js - License: BSD-3-Clause - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 1,536 - Commits in the last 12 months: 361 - Contributors: 142 - Last commit: Oct 3, 2026 - Latest release: v37.4.1 (Oct 3, 2026) - Install (npm): `npm install @kitware/vtk.js`, 284.9K downloads per week - Topics: 3D & scientific visualization ### Overview vtk.js is an open-source JavaScript visualization library released under the BSD-3-Clause license. Its GitHub repository has 1,536 stars, 423 forks, and 142 contributors. It is actively developed with 361 commits in the last 12 months. The latest release, v37.4.1, was published on Oct 3, 2026. On npm it is downloaded about 284.9K times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) Source: https://awesomedataviz.com/tools/vtk-js/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## MSAGL > Microsoft Automatic Graph Layout: tools for graph layout and viewing in .NET. - Category: [C# & .NET charting libraries](https://awesomedataviz.com/categories/dotnet/) - Repository: https://github.com/microsoft/automatic-graph-layout - License: Other - Language: C# - Status: Active (commits in the last 90 days) - GitHub stars: 1,499 - Commits in the last 12 months: 7 - Contributors: 46 - Last commit: Aug 21, 2026 - Latest release: v1.1 (Jan 28, 2022) - Install (NuGet): `dotnet add package Microsoft.Msagl`, 796.7K downloads in total - Topics: Graph & network visualization ### Overview MSAGL is a .NET charting library. Its GitHub repository has 1,499 stars, 317 forks, and 46 contributors. It is actively developed with 7 commits in the last 12 months. The latest release, v1.1, was published on Jan 28, 2022. It has been downloaded about 796.7K times from NuGet. ### Alternatives - [ScottPlot](https://awesomedataviz.com/tools/scottplot/): Interactive plotting library for .NET with WinForms, WPF, Avalonia, Blazor and other controls. (6.8K stars) - [LiveCharts2](https://awesomedataviz.com/tools/livecharts2/): Animated, interactive charts, maps and gauges for .NET UI frameworks. (5.5K stars) - [OxyPlot](https://awesomedataviz.com/tools/oxyplot/): Cross-platform plotting library for .NET. (3.5K stars) - [Microcharts](https://awesomedataviz.com/tools/microcharts/): Simple cross-platform charts for .NET, drawn with SkiaSharp. (2.1K stars) - [Mapsui](https://awesomedataviz.com/tools/mapsui/): .NET map component for MAUI, Avalonia, Uno Platform, Blazor, WPF and WinUI. (1.6K stars) Source: https://awesomedataviz.com/tools/msagl/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Graphviz > Open source graph visualization command line tool and library. From input text to SVG,PDF,interactive web graph browser. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://graphviz.org/ - Repository: https://gitlab.com/graphviz/graphviz - License: EPL-2.0 - Status: Active (commits in the last 90 days) - GitHub stars: 1,473 - Last commit: Oct 4, 2026 - Topics: Graph & network visualization, Diagrams & diagrams as code ### Overview Graphviz is an open-source data visualization app released under the EPL-2.0 license. Its GitLab repository has 1,473 stars and 406 forks. It is actively developed. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) ### Comparisons - [Graphviz vs Mermaid](https://awesomedataviz.com/compare/graphviz-vs-mermaid/) Source: https://awesomedataviz.com/tools/graphviz/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Plotly.rs > Plotly.js-based interactive plotting library for Rust. - Category: [Rust plotting & visualization libraries](https://awesomedataviz.com/categories/rust/) - Website: https://docs.rs/plotly - Repository: https://github.com/plotly/plotly.rs - License: MIT - Language: Rust - Status: Active (commits in the last 90 days) - GitHub stars: 1,457 - Commits in the last 12 months: 53 - Contributors: 53 - Last commit: Jul 27, 2026 - Latest release: 0.14.1 (Feb 15, 2026) - Install (crates.io): `cargo add plotly`, 593K downloads per 90 days ### Overview Plotly.rs is an open-source Rust visualization library released under the MIT license. Its GitHub repository has 1,457 stars, 128 forks, and 53 contributors. It is actively developed with 53 commits in the last 12 months. The latest release, 0.14.1, was published on Feb 15, 2026. On crates.io it is downloaded about 593K times per 90 days. ### Alternatives - [Plotters](https://awesomedataviz.com/tools/plotters/): Drawing library for data plotting in Rust, with bitmap, SVG, WebAssembly and GUI backends. (4.6K stars) - [Charming](https://awesomedataviz.com/tools/charming/): Chart rendering library for Rust powered by Apache ECharts. (2.6K stars) - [malevich](https://awesomedataviz.com/tools/malevich/): Terminal plotting: line, scatter, bar, histogram, heatmap, box plot, violin and more, with automatic axes. (70 stars) ### Comparisons - [Plotly.rs vs Plotters](https://awesomedataviz.com/compare/plotly-rs-vs-plotters/) - [Charming vs Plotly.rs](https://awesomedataviz.com/compare/charming-vs-plotly-rs/) - [malevich vs Plotly.rs](https://awesomedataviz.com/compare/malevich-vs-plotly-rs/) Source: https://awesomedataviz.com/tools/plotly-rs/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Mayavi > Interactive scientific data visualization and 3D plotting in Python. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://docs.enthought.com/mayavi/mayavi/ - Repository: https://github.com/enthought/mayavi - License: BSD-3-Clause - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 1,412 - Commits in the last 12 months: 43 - Contributors: 62 - Last commit: Oct 1, 2026 - Latest release: 4.9.0 (Aug 4, 2026) - Install (PyPI): `pip install mayavi`, 2.1K downloads per week - Topics: 3D & scientific visualization ### Overview Mayavi is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 1,412 stars, 321 forks, and 62 contributors. It is actively developed with 43 commits in the last 12 months. The latest release, 4.9.0, was published on Aug 4, 2026. On PyPI it is downloaded about 2.1K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/mayavi/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Gruff > Graphing library for Ruby that renders charts as images using RMagick. - Category: [Ruby charting libraries](https://awesomedataviz.com/categories/ruby/) - Website: http://gruff.rubyforge.org - Repository: https://github.com/topfunky/gruff - License: MIT - Language: Ruby - Status: Active (commits in the last 90 days) - GitHub stars: 1,398 - Commits in the last 12 months: 37 - Contributors: 43 - Last commit: Sep 6, 2026 - Install (RubyGems): `gem install gruff` ### Overview Gruff is an open-source Ruby charting library released under the MIT license. Its GitHub repository has 1,398 stars, 240 forks, and 43 contributors. It is actively developed with 37 commits in the last 12 months. ### Alternatives - [Chartkick](https://awesomedataviz.com/tools/chartkick/): Create charts with one line of Ruby. (6.5K stars) - [YouPlot](https://awesomedataviz.com/tools/youplot/): Command-line tool that draws plots in the terminal from piped data. (4.9K stars) - [Blazer](https://awesomedataviz.com/tools/blazer/): Business intelligence tool for Rails apps: explore data with SQL and build charts and dashboards. (4.8K stars) ### Comparisons - [Chartkick vs Gruff](https://awesomedataviz.com/compare/chartkick-vs-gruff/) - [Gruff vs YouPlot](https://awesomedataviz.com/compare/gruff-vs-youplot/) - [Blazer vs Gruff](https://awesomedataviz.com/compare/blazer-vs-gruff/) Source: https://awesomedataviz.com/tools/gruff/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## JFreeChart > 2D chart library for Java applications using Swing, JavaFX or server-side rendering. - Category: [Java, Kotlin & Scala visualization libraries](https://awesomedataviz.com/categories/jvm/) - Website: http://www.jfree.org/jfreechart/ - Repository: https://github.com/jfree/jfreechart - License: LGPL-2.1 - Language: Java - Status: Inactive (no commits in over a year) - GitHub stars: 1,391 - Commits in the last 12 months: 0 - Contributors: 30 - Last commit: Jun 7, 2025 - Latest release: v1.5.6 (May 21, 2025) - Install (Maven Central): `implementation("org.jfree:jfreechart:1.5.5")` ### Overview JFreeChart is an open-source JVM charting library released under the LGPL-2.1 license. Its GitHub repository has 1,391 stars, 672 forks, and 30 contributors. It has not had a commit since Jun 7, 2025. The latest release, v1.5.6, was published on May 21, 2025. ### Alternatives - [XChart](https://awesomedataviz.com/tools/xchart/): Lightweight Java library for plotting data. (1.6K stars) - [Kandy](https://awesomedataviz.com/tools/kandy/): Kotlin plotting library with a typed DSL, developed by JetBrains. (746 stars) - [Lets-Plot for Kotlin](https://awesomedataviz.com/tools/lets-plot-for-kotlin/): Grammar of graphics plotting API for Kotlin, built on Lets-Plot. (487 stars) ### Comparisons - [JFreeChart vs XChart](https://awesomedataviz.com/compare/jfreechart-vs-xchart/) - [JFreeChart vs Kandy](https://awesomedataviz.com/compare/jfreechart-vs-kandy/) - [JFreeChart vs Lets-Plot for Kotlin](https://awesomedataviz.com/compare/jfreechart-vs-lets-plot-for-kotlin/) Source: https://awesomedataviz.com/tools/jfreechart/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Mosaic > Framework for linking databases such as DuckDB with interactive views to visualize large datasets. - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://idl.uw.edu/mosaic/ - Repository: https://github.com/uwdata/mosaic - License: BSD-3-Clause - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 1,390 - Commits in the last 12 months: 278 - Contributors: 38 - Last commit: Oct 1, 2026 - Latest release: v0.32.0 (Sep 28, 2026) - Install (npm): `npm install @uwdata/vgplot`, 33.7K downloads per week - Topics: Visualizing large datasets ### Overview Mosaic is an open-source JavaScript visualization library released under the BSD-3-Clause license. Its GitHub repository has 1,390 stars, 124 forks, and 38 contributors. It is actively developed with 278 commits in the last 12 months. The latest release, v0.32.0, was published on Sep 28, 2026. On npm it is downloaded about 33.7K times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) Source: https://awesomedataviz.com/tools/mosaic/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## glumpy > OpenGL scientific visualizations library. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: http://glumpy.github.io - Repository: https://github.com/glumpy/glumpy - License: BSD-3-Clause - Language: Python - Status: Inactive (no commits in over a year) - GitHub stars: 1,280 - Commits in the last 12 months: 0 - Contributors: 52 - Last commit: Jul 15, 2025 - Latest release: v1.2.1 (Dec 4, 2023) - Install (PyPI): `pip install glumpy`, 103 downloads per week - Topics: 3D & scientific visualization, GPU-accelerated & WebGL visualization ### Overview glumpy is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 1,280 stars, 179 forks, and 52 contributors. It has not had a commit since Jul 15, 2025. The latest release, v1.2.1, was published on Dec 4, 2023. On PyPI it is downloaded about 103 times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/glumpy/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ggrepel > Repels overlapping text labels away from each other in ggplot2 plots. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://ggrepel.slowkow.com - Repository: https://github.com/slowkow/ggrepel - License: GPL-3.0 - Language: R - Status: Maintained (commits in the last 12 months) - GitHub stars: 1,261 - Commits in the last 12 months: 30 - Contributors: 21 - Last commit: Apr 14, 2026 - Install (CRAN): `install.packages("ggrepel")`, 94.2K downloads per week - Topics: Grammar of graphics libraries ### Overview ggrepel is an open-source R visualization package released under the GPL-3.0 license. Its GitHub repository has 1,261 stars, 94 forks, and 21 contributors. It is maintained with 30 commits in the last 12 months; the most recent commit was on Apr 14, 2026. On CRAN it is downloaded about 94.2K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/ggrepel/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Victory Native > High-performance charting library for React Native, built on React Native Skia. - Category: [React Native chart libraries](https://awesomedataviz.com/categories/react-native/) - Website: https://commerce.nearform.com/open-source/victory-native - Repository: https://github.com/FormidableLabs/victory-native-xl - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 1,232 - Commits in the last 12 months: 29 - Contributors: 41 - Last commit: Aug 31, 2026 - Latest release: victory-native@42.0.1 (Aug 31, 2026) - Install (npm): `npm install victory-native`, 515.7K downloads per week ### Overview Victory Native is an open-source React Native chart library released under the MIT license. Its GitHub repository has 1,232 stars, 110 forks, and 41 contributors. It is actively developed with 29 commits in the last 12 months. The latest release, victory-native@42.0.1, was published on Aug 31, 2026. On npm it is downloaded about 515.7K times per week. ### Alternatives - [react-native-maps](https://awesomedataviz.com/tools/react-native-maps/): Map view component for iOS and Android in React Native. (16K stars) - [F2](https://awesomedataviz.com/tools/f2/): An elegant, interactive and flexible charting library for mobile, maintained by Alibaba (8K stars) - [React Native Chart Kit](https://awesomedataviz.com/tools/react-native-chart-kit/): Line, bar, pie, progress and contribution graph charts for React Native. (3.1K stars) - [react-native-graph](https://awesomedataviz.com/tools/react-native-graph/): Animated, high-performance line graphs for React Native, built with Skia. (2.6K stars) ### Comparisons - [react-native-maps vs Victory Native](https://awesomedataviz.com/compare/react-native-maps-vs-victory-native/) - [F2 vs Victory Native](https://awesomedataviz.com/compare/f2-vs-victory-native/) - [React Native Chart Kit vs Victory Native](https://awesomedataviz.com/compare/react-native-chart-kit-vs-victory-native/) - [react-native-graph vs Victory Native](https://awesomedataviz.com/compare/react-native-graph-vs-victory-native/) Source: https://awesomedataviz.com/tools/victory-native/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ggraph > Grammar of graphics for graphs and networks, extending ggplot2. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://ggraph.data-imaginist.com - Repository: https://github.com/thomasp85/ggraph - License: MIT - Language: R - Status: Inactive (no commits in over a year) - GitHub stars: 1,118 - Commits in the last 12 months: 0 - Contributors: 15 - Last commit: Aug 25, 2025 - Latest release: v2.2.2 (Aug 25, 2025) - Install (CRAN): `install.packages("ggraph")`, 15.9K downloads per week - Topics: Graph & network visualization, Grammar of graphics libraries ### Overview ggraph is an open-source R visualization package released under the MIT license. Its GitHub repository has 1,118 stars, 114 forks, and 15 contributors. It has not had a commit since Aug 25, 2025. The latest release, v2.2.2, was published on Aug 25, 2025. On CRAN it is downloaded about 15.9K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/ggraph/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Graphin > Graph visualization library powered by React & Typescript (built on top of G6), maintained by Alibaba. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Website: https://github.com/antvis/graphin - Repository: https://github.com/antvis/Graphin - License: MIT - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 1,098 - Commits in the last 12 months: 2 - Contributors: 48 - Last commit: Nov 18, 2025 - Latest release: 3.0.5 (Apr 24, 2025) - Install (npm): `npm install @antv/graphin`, 118.8K downloads per week - Topics: Graph & network visualization ### Overview Graphin is an open-source React chart library released under the MIT license. Its GitHub repository has 1,098 stars, 275 forks, and 48 contributors. It is maintained with 2 commits in the last 12 months; the most recent commit was on Nov 18, 2025. The latest release, 3.0.5, was published on Apr 24, 2025. On npm it is downloaded about 118.8K times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) Source: https://awesomedataviz.com/tools/graphin/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Veusz > Python multiplatform GUI plotting tool and graphing library - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://veusz.github.io/ - Repository: https://github.com/veusz/veusz - License: GPL-2.0 - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 1,051 - Commits in the last 12 months: 41 - Contributors: 40 - Last commit: Aug 22, 2026 - Latest release: veusz-4.2.1 (Apr 4, 2026) - Install (PyPI): `pip install veusz`, 86 downloads per week ### Overview Veusz is an open-source Python visualization library released under the GPL-2.0 license. Its GitHub repository has 1,051 stars, 141 forks, and 40 contributors. It is actively developed with 41 commits in the last 12 months. The latest release, veusz-4.2.1, was published on Apr 4, 2026. On PyPI it is downloaded about 86 times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/veusz/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Mapael > JQuery plugin based on raphael.js to display vector maps. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://www.vincentbroute.fr/mapael/ - Repository: https://github.com/neveldo/jQuery-Mapael - License: MIT - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 1,007 - Commits in the last 12 months: 0 - Contributors: 10 - Last commit: Feb 9, 2022 - Latest release: 2.2.0 (Mar 8, 2018) - Install (npm): `npm install jquery-mapael`, 24.8K downloads per week - Topics: Maps & geospatial visualization ### Overview Mapael is an open-source JavaScript mapping library released under the MIT license. Its GitHub repository has 1,007 stars, 194 forks, and 10 contributors. It has not had a commit since Feb 9, 2022. The latest release, 2.2.0, was published on Mar 8, 2018. On npm it is downloaded about 24.8K times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/mapael/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## GraphicsJS > Lightweight JS graphics library with intuitive API, based on SVG/VML. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: http://www.graphicsjs.org - Repository: https://github.com/AnyChart/GraphicsJS - License: BSD-3-Clause - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 995 - Commits in the last 12 months: 0 - Contributors: 10 - Last commit: Sep 10, 2024 - Latest release: v1.3.5 (Oct 30, 2018) - Install (npm): `npm install graphicsjs`, 933 downloads per week ### Overview GraphicsJS is an open-source JavaScript charting library released under the BSD-3-Clause license. Its GitHub repository has 995 stars, 70 forks, and 10 contributors. It has not had a commit since Sep 10, 2024. The latest release, v1.3.5, was published on Oct 30, 2018. On npm it is downloaded about 933 times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/graphicsjs/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## DecoView > Animated circular wheel chart library. - Category: [Android chart libraries](https://awesomedataviz.com/categories/android/) - Repository: https://github.com/bmarrdev/android-DecoView-charting - License: Apache-2.0 - Language: Java - Status: Inactive (no commits in over a year) - GitHub stars: 984 - Commits in the last 12 months: 0 - Contributors: 1 - Last commit: Jul 9, 2016 - Latest release: v1.2 (Jul 3, 2016) ### Overview DecoView is an open-source Android chart library released under the Apache-2.0 license. Its GitHub repository has 984 stars, 187 forks, and 1 contributor. It has not had a commit since Jul 9, 2016. The latest release, v1.2, was published on Jul 3, 2016. ### Alternatives - [MPAndroidChart](https://awesomedataviz.com/tools/mpandroidchart/): A powerful & easy to use chart library. (38.2K stars) - [HelloCharts](https://awesomedataviz.com/tools/hellocharts/): Android chart library with line, column, pie, bubble and combo charts, plus zoom and scroll. (7.6K stars) - [WilliamChart](https://awesomedataviz.com/tools/williamchart/): Simple chart library. (5.1K stars) - [Vico](https://awesomedataviz.com/tools/vico/): Extensible chart library for Jetpack Compose and Compose Multiplatform. (3.2K stars) ### Comparisons - [DecoView vs MPAndroidChart](https://awesomedataviz.com/compare/decoview-vs-mpandroidchart/) - [DecoView vs HelloCharts](https://awesomedataviz.com/compare/decoview-vs-hellocharts/) - [DecoView vs WilliamChart](https://awesomedataviz.com/compare/decoview-vs-williamchart/) - [DecoView vs Vico](https://awesomedataviz.com/compare/decoview-vs-vico/) Source: https://awesomedataviz.com/tools/decoview/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Leaflet for R > R interface to the Leaflet JavaScript library for interactive maps. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: http://rstudio.github.io/leaflet/ - Repository: https://github.com/rstudio/leaflet - License: MIT - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 841 - Commits in the last 12 months: 0 - Contributors: 40 - Last commit: Sep 30, 2025 - Latest release: v2.2.3 (Sep 4, 2025) - Install (CRAN): `install.packages("leaflet")`, 39.4K downloads per week - Topics: Maps & geospatial visualization ### Overview Leaflet for R is an open-source R visualization package released under the MIT license. Its GitHub repository has 841 stars, 505 forks, and 40 contributors. It has not had a commit since Sep 30, 2025. The latest release, v2.2.3, was published on Sep 4, 2025. On CRAN it is downloaded about 39.4K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/leaflet-for-r/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## DAC > Dashboard-as-code tool that builds interactive dashboards from YAML and TSX definitions - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://getbruin.com/docs/dac/ - Repository: https://github.com/bruin-data/dac - License: AGPL-3.0 - Language: Go - Status: Active (commits in the last 90 days) - GitHub stars: 779 - Commits in the last 12 months: 279 - Contributors: 7 - Last commit: Oct 1, 2026 - Latest release: v0.24.0 (Oct 1, 2026) - Install (Go): `go get github.com/bruin-data/dac` - Topics: Dashboards & BI ### Overview DAC is an open-source data visualization app released under the AGPL-3.0 license. Its GitHub repository has 779 stars, 36 forks, and 7 contributors. It is actively developed with 279 commits in the last 12 months. The latest release, v0.24.0, was published on Oct 1, 2026. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/dac/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Kandy > Kotlin plotting library with a typed DSL, developed by JetBrains. - Category: [Java, Kotlin & Scala visualization libraries](https://awesomedataviz.com/categories/jvm/) - Website: https://kotlin.github.io/kandy/ - Repository: https://github.com/Kotlin/kandy - License: Apache-2.0 - Language: Kotlin - Status: Active (commits in the last 90 days) - GitHub stars: 746 - Commits in the last 12 months: 49 - Contributors: 12 - Last commit: Sep 8, 2026 - Latest release: v0.8.3 (Dec 12, 2025) ### Overview Kandy is an open-source JVM charting library released under the Apache-2.0 license. Its GitHub repository has 746 stars, 27 forks, and 12 contributors. It is actively developed with 49 commits in the last 12 months. The latest release, v0.8.3, was published on Dec 12, 2025. ### Alternatives - [XChart](https://awesomedataviz.com/tools/xchart/): Lightweight Java library for plotting data. (1.6K stars) - [JFreeChart](https://awesomedataviz.com/tools/jfreechart/): 2D chart library for Java applications using Swing, JavaFX or server-side rendering. (1.4K stars) - [Lets-Plot for Kotlin](https://awesomedataviz.com/tools/lets-plot-for-kotlin/): Grammar of graphics plotting API for Kotlin, built on Lets-Plot. (487 stars) ### Comparisons - [Kandy vs XChart](https://awesomedataviz.com/compare/kandy-vs-xchart/) - [JFreeChart vs Kandy](https://awesomedataviz.com/compare/jfreechart-vs-kandy/) - [Kandy vs Lets-Plot for Kotlin](https://awesomedataviz.com/compare/kandy-vs-lets-plot-for-kotlin/) Source: https://awesomedataviz.com/tools/kandy/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Cytoscape > Desktop platform for network analysis and visualization, widely used in bioinformatics. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: http://www.cytoscape.org/ - Repository: https://github.com/cytoscape/cytoscape - Language: Shell - Status: Active (commits in the last 90 days) - GitHub stars: 731 - Commits in the last 12 months: 4 - Contributors: 18 - Last commit: Aug 17, 2026 - Latest release: 3.10.5 (Sep 29, 2026) - Topics: Graph & network visualization ### Overview Cytoscape is a data visualization app. Its GitHub repository has 731 stars, 153 forks, and 18 contributors. It is actively developed with 4 commits in the last 12 months. The latest release, 3.10.5, was published on Sep 29, 2026. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/cytoscape/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## LargeVis > Implementation of the LargeVis paper, used to visualize large-scale and high-dimensional data. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Repository: https://github.com/lferry007/LargeVis - License: Apache-2.0 - Language: C++ - Status: Inactive (no commits in over a year) - GitHub stars: 711 - Commits in the last 12 months: 0 - Contributors: 3 - Last commit: Nov 2, 2016 - Topics: Visualizing large datasets ### Overview LargeVis is an open-source C++ visualization tool released under the Apache-2.0 license. Its GitHub repository has 711 stars, 168 forks, and 3 contributors. It has not had a commit since Nov 2, 2016. ### Alternatives - [ImPlot](https://awesomedataviz.com/tools/implot/): Immediate-mode plotting library for Dear ImGui. (6.2K stars) - [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/): Open-source Qt5 application to plot charts (based on Qwt). (6.2K stars) - [Matplot++](https://awesomedataviz.com/tools/matplotpp/): C++ graphics library for data visualization with a MATLAB-like API. (4.9K stars) - [F3D](https://awesomedataviz.com/tools/f3d/): Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. (4.7K stars) - [Mapnik](https://awesomedataviz.com/tools/mapnik/): Toolkit for rendering maps, widely used to render OpenStreetMap tiles. (4K stars) - [ROOT](https://awesomedataviz.com/tools/root/): CERN framework for analyzing, storing and visualizing large scientific datasets. (3.3K stars) Source: https://awesomedataviz.com/tools/largevis/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ggvis > A data visualization package with a syntax similar to ggplot2 which allows you to create rich interactive graphics. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://ggvis.rstudio.com/ - Repository: https://github.com/rstudio/ggvis - License: GPL-2.0 - Language: R - Status: Archived (the repository is archived and read-only) - GitHub stars: 707 - Commits in the last 12 months: 3 - Contributors: 23 - Last commit: Feb 10, 2026 - Latest release: v0.4.9 (Feb 9, 2024) - Install (CRAN): `install.packages("ggvis")`, 582 downloads per week - Topics: Grammar of graphics libraries ### Overview ggvis is an open-source R visualization package released under the GPL-2.0 license. Its GitHub repository has 707 stars, 165 forks, and 23 contributors. Its repository is archived on GitHub and no longer receives updates. The latest release, v0.4.9, was published on Feb 9, 2024. On CRAN it is downloaded about 582 times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/ggvis/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## pptk > Visualize and work with 2D/3D pointclouds - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://heremaps.github.io/pptk - Repository: https://github.com/heremaps/pptk - License: MIT - Language: C++ - Status: Inactive (no commits in over a year) - GitHub stars: 635 - Commits in the last 12 months: 0 - Contributors: 1 - Last commit: Oct 4, 2018 - Install (PyPI): `pip install pptk`, 61 downloads per week - Topics: 3D & scientific visualization ### Overview pptk is an open-source Python visualization library released under the MIT license. Its GitHub repository has 635 stars, 112 forks, and 1 contributor. It has not had a commit since Oct 4, 2018. On PyPI it is downloaded about 61 times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/pptk/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## visNetwork > Interactive network visualisations - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://datastorm-open.github.io/visNetwork/ - Repository: https://github.com/datastorm-open/visNetwork - License: MIT - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 563 - Commits in the last 12 months: 0 - Contributors: 6 - Last commit: Sep 8, 2025 - Latest release: 2.1.1 (Jan 31, 2022) - Install (CRAN): `install.packages("visNetwork")`, 16.7K downloads per week - Topics: Graph & network visualization ### Overview visNetwork is an open-source R visualization package released under the MIT license. Its GitHub repository has 563 stars, 125 forks, and 6 contributors. It has not had a commit since Sep 8, 2025. The latest release, 2.1.1, was published on Jan 31, 2022. On CRAN it is downloaded about 16.7K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/visnetwork/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## yt > Toolkit for analysis and visualization of volumetric data. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: http://yt-project.org - Repository: https://github.com/yt-project/yt - License: BSD-3-Clause - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 559 - Commits in the last 12 months: 400 - Contributors: 166 - Last commit: Oct 2, 2026 - Latest release: yt-4.4.2 (Nov 18, 2025) - Install (PyPI): `pip install yt`, 4.6K downloads per week - Topics: 3D & scientific visualization ### Overview yt is an open-source Python visualization library released under the BSD-3-Clause license. Its GitHub repository has 559 stars, 321 forks, and 166 contributors. It is actively developed with 400 commits in the last 12 months. The latest release, yt-4.4.2, was published on Nov 18, 2025. On PyPI it is downloaded about 4.6K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/yt/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## VisIt > Visualization and analysis tool for large mesh-based scientific data, developed at LLNL. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Website: https://visit.llnl.gov - Repository: https://github.com/visit-dav/visit - License: BSD-3-Clause - Language: C - Status: Active (commits in the last 90 days) - GitHub stars: 532 - Commits in the last 12 months: 353 - Contributors: 63 - Last commit: Oct 2, 2026 - Latest release: v3.5.0 (Apr 29, 2026) - Topics: 3D & scientific visualization ### Overview VisIt is an open-source C++ visualization tool released under the BSD-3-Clause license. Its GitHub repository has 532 stars, 140 forks, and 63 contributors. It is actively developed with 353 commits in the last 12 months. The latest release, v3.5.0, was published on Apr 29, 2026. ### Alternatives - [ImPlot](https://awesomedataviz.com/tools/implot/): Immediate-mode plotting library for Dear ImGui. (6.2K stars) - [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/): Open-source Qt5 application to plot charts (based on Qwt). (6.2K stars) - [Matplot++](https://awesomedataviz.com/tools/matplotpp/): C++ graphics library for data visualization with a MATLAB-like API. (4.9K stars) - [F3D](https://awesomedataviz.com/tools/f3d/): Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. (4.7K stars) - [Mapnik](https://awesomedataviz.com/tools/mapnik/): Toolkit for rendering maps, widely used to render OpenStreetMap tiles. (4K stars) - [ROOT](https://awesomedataviz.com/tools/root/): CERN framework for analyzing, storing and visualizing large scientific datasets. (3.3K stars) Source: https://awesomedataviz.com/tools/visit/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Lets-Plot for Kotlin > Grammar of graphics plotting API for Kotlin, built on Lets-Plot. - Category: [Java, Kotlin & Scala visualization libraries](https://awesomedataviz.com/categories/jvm/) - Website: https://lets-plot.org/kotlin/ - Repository: https://github.com/JetBrains/lets-plot-kotlin - License: MIT - Language: Kotlin - Status: Maintained (commits in the last 12 months) - GitHub stars: 487 - Commits in the last 12 months: 129 - Contributors: 15 - Last commit: Jul 1, 2026 - Latest release: v4.15.0 (Jun 30, 2026) - Install (Maven Central): `implementation("org.jetbrains.lets-plot:lets-plot-kotlin-jvm:4.10.0")` - Topics: Jupyter & notebook visualization, Grammar of graphics libraries ### Overview Lets-Plot for Kotlin is an open-source JVM charting library released under the MIT license. Its GitHub repository has 487 stars, 39 forks, and 15 contributors. It is maintained with 129 commits in the last 12 months; the most recent commit was on Jul 1, 2026. The latest release, v4.15.0, was published on Jun 30, 2026. ### Alternatives - [XChart](https://awesomedataviz.com/tools/xchart/): Lightweight Java library for plotting data. (1.6K stars) - [JFreeChart](https://awesomedataviz.com/tools/jfreechart/): 2D chart library for Java applications using Swing, JavaFX or server-side rendering. (1.4K stars) - [Kandy](https://awesomedataviz.com/tools/kandy/): Kotlin plotting library with a typed DSL, developed by JetBrains. (746 stars) ### Comparisons - [Lets-Plot for Kotlin vs XChart](https://awesomedataviz.com/compare/lets-plot-for-kotlin-vs-xchart/) - [JFreeChart vs Lets-Plot for Kotlin](https://awesomedataviz.com/compare/jfreechart-vs-lets-plot-for-kotlin/) - [Kandy vs Lets-Plot for Kotlin](https://awesomedataviz.com/compare/kandy-vs-lets-plot-for-kotlin/) Source: https://awesomedataviz.com/tools/lets-plot-for-kotlin/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## LabPlot > KDE application for interactive scientific plotting, data analysis and visualization. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://invent.kde.org/education/labplot - Repository: https://github.com/KDE/labplot - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 486 - Commits in the last 12 months: 1,428 - Contributors: 61 - Last commit: Oct 4, 2026 - Topics: 3D & scientific visualization ### Overview LabPlot is a data visualization app. Its GitHub repository has 486 stars, 67 forks, and 61 contributors. It is actively developed with 1,428 commits in the last 12 months. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/labplot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## TTK > Topological data analysis and visualization. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Website: https://topology-tool-kit.github.io/ - Repository: https://github.com/topology-tool-kit/ttk - License: BSD-3-Clause - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 481 - Commits in the last 12 months: 480 - Contributors: 46 - Last commit: Oct 3, 2026 - Latest release: 1.4.0 (Aug 6, 2026) - Topics: 3D & scientific visualization ### Overview TTK is an open-source C++ visualization tool released under the BSD-3-Clause license. Its GitHub repository has 481 stars, 131 forks, and 46 contributors. It is actively developed with 480 commits in the last 12 months. The latest release, 1.4.0, was published on Aug 6, 2026. ### Alternatives - [ImPlot](https://awesomedataviz.com/tools/implot/): Immediate-mode plotting library for Dear ImGui. (6.2K stars) - [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/): Open-source Qt5 application to plot charts (based on Qwt). (6.2K stars) - [Matplot++](https://awesomedataviz.com/tools/matplotpp/): C++ graphics library for data visualization with a MATLAB-like API. (4.9K stars) - [F3D](https://awesomedataviz.com/tools/f3d/): Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. (4.7K stars) - [Mapnik](https://awesomedataviz.com/tools/mapnik/): Toolkit for rendering maps, widely used to render OpenStreetMap tiles. (4K stars) - [ROOT](https://awesomedataviz.com/tools/root/): CERN framework for analyzing, storing and visualizing large scientific datasets. (3.3K stars) Source: https://awesomedataviz.com/tools/ttk/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## uniplot > Lightweight plotting to the terminal. 4x resolution via Unicode. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Repository: https://github.com/olavolav/uniplot - License: MIT - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 460 - Commits in the last 12 months: 31 - Contributors: 7 - Last commit: Aug 6, 2026 - Latest release: v0.23.2 (Jul 12, 2026) - Install (PyPI): `pip install uniplot`, 27.8K downloads per week - Topics: Terminal & command-line charts ### Overview uniplot is an open-source Python visualization library released under the MIT license. Its GitHub repository has 460 stars, 24 forks, and 7 contributors. It is actively developed with 31 commits in the last 12 months. The latest release, v0.23.2, was published on Jul 12, 2026. On PyPI it is downloaded about 27.8K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/uniplot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Toyplot > The kid-sized plotting toolkit for Python with grownup-sized goals. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://toyplot.readthedocs.io/en/stable/ - Repository: https://github.com/sandialabs/toyplot - License: BSD - Language: Jupyter Notebook - Status: Maintained (commits in the last 12 months) - GitHub stars: 449 - Commits in the last 12 months: 26 - Contributors: 9 - Last commit: May 4, 2026 - Latest release: v2.1.0 (Mar 19, 2026) - Install (PyPI): `pip install toyplot`, 1.1K downloads per week ### Overview Toyplot is an open-source Python visualization library released under the BSD license. Its GitHub repository has 449 stars, 40 forks, and 9 contributors. It is maintained with 26 commits in the last 12 months; the most recent commit was on May 4, 2026. The latest release, v2.1.0, was published on Mar 19, 2026. On PyPI it is downloaded about 1.1K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/toyplot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## diagram > Text mode diagrams using UTF-8 characters - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://pypi.org/project/diagram/ - Repository: https://github.com/tehmaze/diagram - License: MIT - Language: Python - Status: Inactive (no commits in over a year) - GitHub stars: 408 - Commits in the last 12 months: 0 - Contributors: 8 - Last commit: Apr 12, 2022 - Install (PyPI): `pip install diagram`, 4.2K downloads per week - Topics: Terminal & command-line charts ### Overview diagram is an open-source Python visualization library released under the MIT license. Its GitHub repository has 408 stars, 22 forks, and 8 contributors. It has not had a commit since Apr 12, 2022. On PyPI it is downloaded about 4.2K times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/diagram/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Quibbler > Your data and anything you plot is effortlessly live and interactive. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Repository: https://github.com/Technion-Kishony-lab/quibbler - License: MIT - Language: Python - Status: Inactive (no commits in over a year) - GitHub stars: 332 - Commits in the last 12 months: 0 - Contributors: 5 - Last commit: Aug 29, 2025 - Latest release: 1.0.1 (Apr 19, 2025) - Install (PyPI): `pip install pyquibbler`, 34 downloads per week - Topics: Jupyter & notebook visualization ### Overview Quibbler is an open-source Python visualization library released under the MIT license. Its GitHub repository has 332 stars, 8 forks, and 5 contributors. It has not had a commit since Aug 29, 2025. The latest release, 1.0.1, was published on Apr 19, 2025. On PyPI it is downloaded about 34 times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/quibbler/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## rbokeh > R Interface to Bokeh. - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://hafen.github.io/rbokeh/ - Repository: https://github.com/bokeh/rbokeh - License: MIT - Language: R - Status: Archived (the repository is archived and read-only) - GitHub stars: 311 - Commits in the last 12 months: 0 - Contributors: 7 - Last commit: Nov 1, 2023 - Install (CRAN): `install.packages("rbokeh")`, 13 downloads per week ### Overview rbokeh is an open-source R visualization package released under the MIT license. Its GitHub repository has 311 stars, 63 forks, and 7 contributors. Its repository is archived on GitHub and no longer receives updates. On CRAN it is downloaded about 13 times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/rbokeh/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## PGFPlots > TeX package for drawing 2D and 3D plots directly in LaTeX documents. - Category: [Diagrams as code](https://awesomedataviz.com/categories/diagrams-as-code/) - Website: http://pgfplots.sourceforge.net/ - Repository: https://github.com/pgf-tikz/pgfplots - Language: TeX - Status: Active (commits in the last 90 days) - GitHub stars: 257 - Commits in the last 12 months: 13 - Contributors: 22 - Last commit: Aug 26, 2026 - Latest release: 1.18.3 (Aug 26, 2026) - Topics: 3D & scientific visualization ### Overview PGFPlots is a diagram-as-code tool. Its GitHub repository has 257 stars, 38 forks, and 22 contributors. It is actively developed with 13 commits in the last 12 months. The latest release, 1.18.3, was published on Aug 26, 2026. ### Alternatives - [Mermaid](https://awesomedataviz.com/tools/mermaid/): Generate diagrams and flowcharts from markdown-like text definitions, with a live editor. (90.5K stars) - [Diagrams](https://awesomedataviz.com/tools/diagrams/): Diagram as code in Python for prototyping cloud system architectures. (42.7K stars) - [D2](https://awesomedataviz.com/tools/d2/): Declarative diagram scripting language that turns text into diagrams. (25.6K stars) - [PlantUML](https://awesomedataviz.com/tools/plantuml/): Generates UML, Gantt, mind map and other diagrams from plain text. (13.4K stars) - [Markmap](https://awesomedataviz.com/tools/markmap/): Builds interactive mind maps from Markdown. (13.1K stars) - [flowchart.js](https://awesomedataviz.com/tools/flowchart-js/): Draws SVG flowcharts from a textual description. (8.7K stars) Source: https://awesomedataviz.com/tools/pgfplots/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Vizdom > A declarative graph layout and rendering engine for Javascript/Typescript powered by Rust/WebAssembly. - Category: [JavaScript graph & network visualization libraries](https://awesomedataviz.com/categories/javascript-graph-visualization/) - Website: https://vizdom.dev - Repository: https://github.com/vizdom-dev/vizdom - License: Apache-2.0 - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 193 - Commits in the last 12 months: 0 - Contributors: 2 - Last commit: Feb 16, 2025 - Topics: Graph & network visualization, Diagrams & diagrams as code ### Overview Vizdom is an open-source JavaScript graph visualization library released under the Apache-2.0 license. Its GitHub repository has 193 stars, 6 forks, and 2 contributors. It has not had a commit since Feb 16, 2025. ### Alternatives - [xyflow](https://awesomedataviz.com/tools/xyflow/): React Flow and Svelte Flow: libraries for building node-based editors, flow charts and interactive diagrams. (38.6K stars) - [G6](https://awesomedataviz.com/tools/g6/): Graph visualization library powered by Javascript & Typescript, maintained by Alibaba (12.3K stars) - [Sigma.js](https://awesomedataviz.com/tools/sigma-js/): JavaScript library dedicated to graph drawing. (12.2K stars) - [Cytoscape.js](https://awesomedataviz.com/tools/cytoscape-js/): JavaScript library for graph drawing maintained by Cytoscape core developers. (11.2K stars) - [Vue Flow](https://awesomedataviz.com/tools/vue-flow/): Flowchart and node-based graph component for Vue 3. (6.9K stars) - [X6](https://awesomedataviz.com/tools/x6/): Diagramming library for DAGs, ER diagrams, flowcharts and other graph editors, maintained by Alibaba. (6.7K stars) Source: https://awesomedataviz.com/tools/vizdom/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Pharos AI > Open-source OSINT conflict-tracking dashboard with geospatial visualization using Deck.gl, MapLibre, and React. (Source Code) - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://conflicts.app - Repository: https://github.com/Juliusolsson05/pharos-ai - License: AGPL-3.0 - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 182 - Commits in the last 12 months: 477 - Contributors: 4 - Last commit: May 16, 2026 - Latest release: db-snapshot-latest (Mar 15, 2026) - Topics: Maps & geospatial visualization, Dashboards & BI ### Overview Pharos AI is an open-source JavaScript mapping library released under the AGPL-3.0 license. Its GitHub repository has 182 stars, 37 forks, and 4 contributors. It is maintained with 477 commits in the last 12 months; the most recent commit was on May 16, 2026. The latest release, db-snapshot-latest, was published on Mar 15, 2026. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/pharos-ai/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Comet > An MLOps platform for tracking, visualizing, and debugging your machine learning workflows from training straight through to production. - Category: [Machine learning visualization tools](https://awesomedataviz.com/categories/machine-learning/) - Repository: https://github.com/comet-ml/comet-examples - License: MIT - Language: Jupyter Notebook - Status: Active (commits in the last 90 days) - GitHub stars: 175 - Commits in the last 12 months: 38 - Contributors: 26 - Last commit: Aug 12, 2026 - Install (PyPI): `pip install comet-ml`, 77.5K downloads per week - Topics: Machine learning & AI visualization ### Overview Comet is an open-source ML visualization tool released under the MIT license. Its GitHub repository has 175 stars, 69 forks, and 26 contributors. It is actively developed with 38 commits in the last 12 months. On PyPI it is downloaded about 77.5K times per week. ### Alternatives - [Netron](https://awesomedataviz.com/tools/netron/): Viewer for neural network, deep learning and machine learning models. (33.5K stars) - [PlotNeuralNet](https://awesomedataviz.com/tools/plotneuralnet/): LaTeX code for drawing neural network architecture diagrams. (25K stars) - [Opik](https://awesomedataviz.com/tools/opik/): Formerly CometLLM. Debug, evaluate, and monitor LLM applications with tracing and dashboards. (22.4K stars) - [Phoenix](https://awesomedataviz.com/tools/phoenix/): ML observability in a notebook with UMAP visualizations (11.7K stars) - [FiftyOne](https://awesomedataviz.com/tools/fiftyone/): Tool for visualizing, curating and evaluating computer vision datasets and models. (11.1K stars) - [Visdom](https://awesomedataviz.com/tools/visdom/): Tool for real-time visualization and monitoring of live data such as ML experiments. (10.3K stars) Source: https://awesomedataviz.com/tools/comet/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ipychart > The power of Chart.js in Jupyter Notebook. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://nicohlr.github.io/ipychart/ - Repository: https://github.com/nicohlr/ipychart - License: MIT - Language: Python - Status: Inactive (no commits in over a year) - GitHub stars: 133 - Commits in the last 12 months: 0 - Contributors: 2 - Last commit: Aug 24, 2024 - Latest release: v0.5.2 (Aug 27, 2024) - Install (npm): `npm install ipychart`, 8 downloads per week - Install (PyPI): `pip install ipychart`, 181 downloads per week - Topics: Jupyter & notebook visualization ### Overview ipychart is an open-source Python visualization library released under the MIT license. Its GitHub repository has 133 stars, 11 forks, and 2 contributors. It has not had a commit since Aug 24, 2024. The latest release, v0.5.2, was published on Aug 27, 2024. On npm it is downloaded about 8 times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/ipychart/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## sankeydiagram.net > Web app for creating and sharing Sankey diagrams of flows and budgets without code. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://sankeydiagram.net/ - Repository: https://github.com/nxt3AT/sankeydiagram.net - License: MIT + Commons Clause - Language: HTML - Status: Active (commits in the last 90 days) - GitHub stars: 123 - Commits in the last 12 months: 2 - Contributors: 4 - Last commit: Aug 20, 2026 - Latest release: v1.7.0 (Aug 10, 2025) - Topics: Diagrams & diagrams as code ### Overview sankeydiagram.net is a data visualization app. Its GitHub repository has 123 stars, 16 forks, and 4 contributors. It is actively developed with 2 commits in the last 12 months. The latest release, v1.7.0, was published on Aug 10, 2025. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/sankeydiagram-net/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## three.py > Easy to use 3D library based on PyOpenGL. Inspired by Three.js. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Repository: https://github.com/stemkoski/three.py - License: MIT - Language: Python - Status: Inactive (no commits in over a year) - GitHub stars: 121 - Commits in the last 12 months: 0 - Contributors: 3 - Last commit: May 30, 2019 - Topics: 3D & scientific visualization, GPU-accelerated & WebGL visualization ### Overview three.py is an open-source Python visualization library released under the MIT license. Its GitHub repository has 121 stars, 26 forks, and 3 contributors. It has not had a commit since May 30, 2019. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/three-py/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## rgl > 3D Visualization Using OpenGL - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://cran.r-project.org/web/packages/rgl/index.html - Repository: https://github.com/dmurdoch/rgl - License: GPL-2.0 - Language: C++ - Status: Active (commits in the last 90 days) - GitHub stars: 103 - Commits in the last 12 months: 36 - Contributors: 12 - Last commit: Jul 15, 2026 - Latest release: v1.3.36 (Mar 6, 2026) - Install (CRAN): `install.packages("rgl")`, 16.7K downloads per week - Topics: 3D & scientific visualization, GPU-accelerated & WebGL visualization ### Overview rgl is an open-source R visualization package released under the GPL-2.0 license. Its GitHub repository has 103 stars, 24 forks, and 12 contributors. It is actively developed with 36 commits in the last 12 months. The latest release, v1.3.36, was published on Mar 6, 2026. On CRAN it is downloaded about 16.7K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/rgl/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## dxcharts-lite > Flexible financial charting library based on HTML5 canvas. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://devexperts.com/dxcharts/ - Repository: https://github.com/devexperts/dxcharts-lite - License: MPL-2.0 - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 101 - Commits in the last 12 months: 3,699 - Contributors: 18 - Last commit: Sep 22, 2026 - Latest release: v2.7.37 (Sep 22, 2026) - Install (npm): `npm install @devexperts/dxcharts-lite`, 8.5K downloads per week - Topics: Financial & stock charts ### Overview dxcharts-lite is an open-source JavaScript charting library released under the MPL-2.0 license. Its GitHub repository has 101 stars, 17 forks, and 18 contributors. It is actively developed with 3,699 commits in the last 12 months. The latest release, v2.7.37, was published on Sep 22, 2026. On npm it is downloaded about 8.5K times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) ### Comparisons - [dxcharts-lite vs Lightweight Charts](https://awesomedataviz.com/compare/dxcharts-lite-vs-lightweight-charts/) Source: https://awesomedataviz.com/tools/dxcharts-lite/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## L7 Plot > Geospatial Visualization Chart Library, maintained by Alibaba - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://l7plot.antv.antgroup.com - Repository: https://github.com/antvis/L7Plot - License: MIT - Language: TypeScript - Status: Inactive (no commits in over a year) - GitHub stars: 91 - Commits in the last 12 months: 0 - Contributors: 13 - Last commit: Jul 15, 2024 - Latest release: @antv/l7plot@0.5.11 (Jul 15, 2024) - Install (npm): `npm install @antv/l7plot`, 23.6K downloads per week - Topics: Maps & geospatial visualization ### Overview L7 Plot is an open-source JavaScript mapping library released under the MIT license. Its GitHub repository has 91 stars, 21 forks, and 13 contributors. It has not had a commit since Jul 15, 2024. The latest release, @antv/l7plot@0.5.11, was published on Jul 15, 2024. On npm it is downloaded about 23.6K times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/l7-plot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## lattice > Trellis graphics for R - Category: [R data visualization packages](https://awesomedataviz.com/categories/r/) - Website: https://lattice.r-forge.r-project.org - Repository: https://github.com/deepayan/lattice - License: GPL-2.0-or-later - Language: R - Status: Active (commits in the last 90 days) - GitHub stars: 74 - Commits in the last 12 months: 16 - Contributors: 10 - Last commit: Aug 9, 2026 - Install (CRAN): `install.packages("lattice")`, 50.6K downloads per week ### Overview lattice is an open-source R visualization package released under the GPL-2.0-or-later license. Its GitHub repository has 74 stars, 19 forks, and 10 contributors. It is actively developed with 16 commits in the last 12 months. On CRAN it is downloaded about 50.6K times per week. ### Alternatives - [ggplot2](https://awesomedataviz.com/tools/ggplot2/): A plotting system based on the grammar of graphics. (7K stars) - [Shiny](https://awesomedataviz.com/tools/shiny/): Framework for creating interactive applications/visualisations (5.7K stars) - [plotly (R)](https://awesomedataviz.com/tools/plotly-r/): Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams (2.7K stars) - [patchwork](https://awesomedataviz.com/tools/patchwork/): Composes multiple ggplot2 plots into a single figure. (2.6K stars) - [ggstatsplot](https://awesomedataviz.com/tools/ggstatsplot/): Ggplot2-based plots with statistical test details included in the graphic. (2.2K stars) - [rayshader](https://awesomedataviz.com/tools/rayshader/): 2D and 3D mapping and data visualization in R, including 3D renders of ggplot2 plots. (2.2K stars) Source: https://awesomedataviz.com/tools/lattice/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## malevich > Terminal plotting: line, scatter, bar, histogram, heatmap, box plot, violin and more, with automatic axes. - Category: [Rust plotting & visualization libraries](https://awesomedataviz.com/categories/rust/) - Website: https://shergin.github.io/malevich/ - Repository: https://github.com/shergin/malevich - License: Apache-2.0 - Language: Rust - Status: Active (commits in the last 90 days) - GitHub stars: 70 - Commits in the last 12 months: 288 - Contributors: 2 - Last commit: Oct 3, 2026 - Latest release: v1.21.0 (Sep 7, 2026) - Install (crates.io): `cargo add malevich`, 1.9K downloads per 90 days - Topics: Terminal & command-line charts ### Overview malevich is an open-source Rust visualization library released under the Apache-2.0 license. Its GitHub repository has 70 stars, 3 forks, and 2 contributors. It is actively developed with 288 commits in the last 12 months. The latest release, v1.21.0, was published on Sep 7, 2026. On crates.io it is downloaded about 1.9K times per 90 days. ### Alternatives - [Plotters](https://awesomedataviz.com/tools/plotters/): Drawing library for data plotting in Rust, with bitmap, SVG, WebAssembly and GUI backends. (4.6K stars) - [Charming](https://awesomedataviz.com/tools/charming/): Chart rendering library for Rust powered by Apache ECharts. (2.6K stars) - [Plotly.rs](https://awesomedataviz.com/tools/plotly-rs/): Plotly.js-based interactive plotting library for Rust. (1.5K stars) ### Comparisons - [malevich vs Plotters](https://awesomedataviz.com/compare/malevich-vs-plotters/) - [Charming vs malevich](https://awesomedataviz.com/compare/charming-vs-malevich/) - [malevich vs Plotly.rs](https://awesomedataviz.com/compare/malevich-vs-plotly-rs/) Source: https://awesomedataviz.com/tools/malevich/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## React Svg Textures > Textures.js ported to React. Fully isomorphic. - Category: [React chart & visualization libraries](https://awesomedataviz.com/categories/react/) - Repository: https://github.com/finnfiddle/react-svg-textures - License: MIT - Language: JavaScript - Status: Inactive (no commits in over a year) - GitHub stars: 32 - Commits in the last 12 months: 0 - Contributors: 2 - Last commit: Apr 17, 2018 - Install (npm): `npm install react-svg-textures`, 236 downloads per week ### Overview React Svg Textures is an open-source React chart library released under the MIT license. Its GitHub repository has 32 stars, 6 forks, and 2 contributors. It has not had a commit since Apr 17, 2018. On npm it is downloaded about 236 times per week. ### Alternatives - [Recharts](https://awesomedataviz.com/tools/recharts/): Declarative react components to render D3 charts. (27.6K stars) - [visx](https://awesomedataviz.com/tools/visx/): Low-level visualization components that combine D3 with React, by Airbnb. (21.1K stars) - [Tremor](https://awesomedataviz.com/tools/tremor/): React components for building charts and dashboards, based on Recharts and Tailwind CSS. (16.5K stars) - [nivo](https://awesomedataviz.com/tools/nivo/): Supercharged dataviz components for React with isomorphic ability, demo. (14.1K stars) - [Victory](https://awesomedataviz.com/tools/victory/): Composable components for building interactive data visualizations (11.2K stars) - [React-vis](https://awesomedataviz.com/tools/react-vis/): React components to build data visualizations. (8.8K stars) Source: https://awesomedataviz.com/tools/react-svg-textures/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## syd > A package for making GUIs around matplotlib figures easy, fast, and streamlined. - Category: [Python data visualization libraries](https://awesomedataviz.com/categories/python/) - Website: https://shareyourdata.readthedocs.io - Repository: https://github.com/landoskape/syd - License: GPL-3.0 - Language: Python - Status: Active (commits in the last 90 days) - GitHub stars: 30 - Commits in the last 12 months: 12 - Contributors: 1 - Last commit: Aug 11, 2026 - Latest release: v1.3.2 (Aug 11, 2026) - Install (PyPI): `pip install syd`, 11 downloads per week ### Overview syd is an open-source Python visualization library released under the GPL-3.0 license. Its GitHub repository has 30 stars, 0 forks, and 1 contributor. It is actively developed with 12 commits in the last 12 months. The latest release, v1.3.2, was published on Aug 11, 2026. On PyPI it is downloaded about 11 times per week. ### Alternatives - [Streamlit](https://awesomedataviz.com/tools/streamlit/): Framework for turning Python scripts into interactive data apps. (45.9K stars) - [Dash](https://awesomedataviz.com/tools/dash/): Framework for building data apps and dashboards in Python, built on Plotly.js and React. (24.4K stars) - [Matplotlib](https://awesomedataviz.com/tools/matplotlib/): 2D plotting library. (23.3K stars) - [Bokeh](https://awesomedataviz.com/tools/bokeh/): Interactive Web Plotting for Python. (20.5K stars) - [Taipy](https://awesomedataviz.com/tools/taipy/): Python framework for building data and AI web applications with interactive charts and dashboards. (19.4K stars) - [Plotly (Python)](https://awesomedataviz.com/tools/plotly-python/): Interactive web based visualization built on top of plotly.js (18.8K stars) Source: https://awesomedataviz.com/tools/syd/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Dipper > Map application development framework powered by L7, maintained by Alibaba. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://dipper.antv.vision - Repository: https://github.com/antvis/Dipper - License: MIT - Language: TypeScript - Status: Archived (the repository is archived and read-only) - GitHub stars: 29 - Commits in the last 12 months: 0 - Contributors: 5 - Last commit: Jul 7, 2022 - Install (npm): `npm install @antv/dipper`, 16 downloads per week - Topics: Maps & geospatial visualization ### Overview Dipper is an open-source JavaScript mapping library released under the MIT license. Its GitHub repository has 29 stars, 7 forks, and 5 contributors. Its repository is archived on GitHub and no longer receives updates. On npm it is downloaded about 16 times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/dipper/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Squey > Visualization software for exploring and understanding large amounts of tabular data (using parallel coordinates, timeseries and scatter plots). - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://squey.org - Repository: https://gitlab.com/squey/squey - License: MIT - Status: Active (commits in the last 90 days) - GitHub stars: 23 - Last commit: Sep 30, 2026 - Topics: Visualizing large datasets, Exploratory data analysis tools ### Overview Squey is an open-source data visualization app released under the MIT license. Its GitLab repository has 23 stars and 3 forks. It is actively developed. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/squey/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## lit-line > SVG Line Chart Web Component - light, fast, interactive & fully responsive. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://apinet.github.io - Repository: https://github.com/apinet/lit-line - License: MIT - Language: TypeScript - Status: Inactive (no commits in over a year) - GitHub stars: 22 - Commits in the last 12 months: 0 - Contributors: 1 - Last commit: Dec 18, 2024 - Latest release: v3.0.0 (Feb 24, 2024) - Install (npm): `npm install lit-line`, 1 downloads per week - Topics: Time series & real-time charts ### Overview lit-line is an open-source JavaScript charting library released under the MIT license. Its GitHub repository has 22 stars, 0 forks, and 1 contributor. It has not had a commit since Dec 18, 2024. The latest release, v3.0.0, was published on Feb 24, 2024. On npm it is downloaded about 1 times per week. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/lit-line/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## gp-treemap > Open source HTML canvas treemap component supporting millions of nodes, and some functional resource usage tools, like disk and S3 usage visualization (GrandPerspective-style) - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Repository: https://github.com/imbue-ai/gp-treemap - License: GPL-2.0 - Language: HTML - Status: Maintained (commits in the last 12 months) - GitHub stars: 10 - Commits in the last 12 months: 184 - Contributors: 1 - Last commit: May 20, 2026 - Latest release: v0.6.2 (May 19, 2026) - Install (npm): `npm install @imbue-ai/gp-treemap`, 9 downloads per week - Topics: Visualizing large datasets ### Overview gp-treemap is an open-source JavaScript visualization library released under the GPL-2.0 license. Its GitHub repository has 10 stars, 1 fork, and 1 contributor. It is maintained with 184 commits in the last 12 months; the most recent commit was on May 20, 2026. The latest release, v0.6.2, was published on May 19, 2026. On npm it is downloaded about 9 times per week. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) Source: https://awesomedataviz.com/tools/gp-treemap/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ODataMap > Interactive scientific research data map. Visualizes 250M+ papers across 7 knowledge continents using D3.js. Demo - Category: [More JavaScript visualization libraries](https://awesomedataviz.com/categories/javascript-visualization-tools/) - Website: https://odatamap.cherishchen2510.workers.dev - Repository: https://github.com/CherishChenCherish/odatamap - License: MIT - Language: TypeScript - Status: Maintained (commits in the last 12 months) - GitHub stars: 10 - Commits in the last 12 months: 20 - Contributors: 0 - Last commit: Apr 4, 2026 - Latest release: v1.0.0 (Apr 2, 2026) ### Overview ODataMap is an open-source JavaScript visualization library released under the MIT license. Its GitHub repository has 10 stars and 0 forks. It is maintained with 20 commits in the last 12 months; the most recent commit was on Apr 4, 2026. The latest release, v1.0.0, was published on Apr 2, 2026. ### Alternatives - [blessed-contrib](https://awesomedataviz.com/tools/blessed-contrib/): Terminal dashboards with charts, maps, gauges and tables, built with Node.js and ASCII/ANSI art. (15.8K stars) - [Vega](https://awesomedataviz.com/tools/vega/): Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. (12K stars) - [Perspective](https://awesomedataviz.com/tools/perspective/): Interactive analytics and visualization component for large and streaming datasets, built on WebAssembly. (11.3K stars) - [vue-echarts](https://awesomedataviz.com/tools/vue-echarts/): Vue.js component for Apache ECharts. (10.8K stars) - [Textures.js](https://awesomedataviz.com/tools/textures-js/): A library to create SVG patterns. (6.1K stars) - [vue-chartjs](https://awesomedataviz.com/tools/vue-chartjs/): Vue.js wrapper for Chart.js. (5.7K stars) Source: https://awesomedataviz.com/tools/odatamap/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Resseract Lite > A Data Analytics and Visualization Tool with flexible architecture to visualize and analyse data - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Repository: https://github.com/abistarun/resseract-lite - License: Apache-2.0 - Language: Java - Status: Inactive (no commits in over a year) - GitHub stars: 7 - Commits in the last 12 months: 0 - Contributors: 1 - Last commit: Aug 24, 2024 - Latest release: resseract-1.0.2 (Aug 24, 2024) ### Overview Resseract Lite is an open-source data visualization app released under the Apache-2.0 license. Its GitHub repository has 7 stars, 0 forks, and 1 contributor. It has not had a commit since Aug 24, 2024. The latest release, resseract-1.0.2, was published on Aug 24, 2024. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/resseract-lite/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## VectorAtlas > Free, 80KB SVG world map with one path per country, id-keyed by ISO 3166-1 alpha-2 code, ready for choropleths. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://vectoratlas.menelabs.com/ - Repository: https://github.com/melenaos/Menelabs.VectorAtlas - License: CC-BY-4.0 - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 5 - Commits in the last 12 months: 11 - Contributors: 1 - Last commit: Aug 17, 2026 - Topics: Maps & geospatial visualization ### Overview VectorAtlas is a JavaScript mapping library. Its GitHub repository has 5 stars, 0 forks, and 1 contributor. It is actively developed with 11 commits in the last 12 months. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/vectoratlas/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Glyph > Deterministic chart library that renders the same JSON spec to identical SVG on every platform, with DuckDB inside and an MCP server for AI agents. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://seanhanca.github.io/glyph/ - Repository: https://github.com/seanhanca/glyph - License: Apache-2.0 - Language: HTML - Status: Maintained (commits in the last 12 months) - GitHub stars: 3 - Commits in the last 12 months: 258 - Contributors: 1 - Last commit: Jun 5, 2026 - Latest release: v0.3.0 (May 28, 2026) - Topics: Grammar of graphics libraries ### Overview Glyph is an open-source JavaScript charting library released under the Apache-2.0 license. Its GitHub repository has 3 stars, 1 fork, and 1 contributor. It is maintained with 258 commits in the last 12 months; the most recent commit was on Jun 5, 2026. The latest release, v0.3.0, was published on May 28, 2026. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/glyph/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Globedots > Dot-matrix WebGL2 globe in 17 kB with markers, arcs, labels, heat maps, and a day-night line. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://swamoth.github.io/globedots/ - Repository: https://github.com/swamoth/globedots - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 1 - Commits in the last 12 months: 33 - Contributors: 1 - Last commit: Sep 18, 2026 - Install (npm): `npm install globedots`, 13 downloads per week - Topics: Maps & geospatial visualization, GPU-accelerated & WebGL visualization ### Overview Globedots is an open-source JavaScript mapping library released under the MIT license. Its GitHub repository has 1 star, 0 forks, and 1 contributor. It is actively developed with 33 commits in the last 12 months. On npm it is downloaded about 13 times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/globedots/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ink-uplot > Render uPlot charts in the terminal (React Ink) with truecolor Unicode and kitty/sixel/iTerm2 graphics. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Repository: https://github.com/planadecu/ink-uplot - License: MIT - Language: TypeScript - Status: Active (commits in the last 90 days) - GitHub stars: 1 - Commits in the last 12 months: 81 - Contributors: 1 - Last commit: Sep 30, 2026 - Latest release: v0.2.16 (Sep 29, 2026) - Install (npm): `npm install ink-uplot`, 526 downloads per week - Topics: Terminal & command-line charts ### Overview ink-uplot is an open-source data visualization app released under the MIT license. Its GitHub repository has 1 star, 0 forks, and 1 contributor. It is actively developed with 81 commits in the last 12 months. The latest release, v0.2.16, was published on Sep 29, 2026. On npm it is downloaded about 526 times per week. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/ink-uplot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## CanvasGlobe > Interactive Canvas 2D globes and flat world maps for JavaScript and React. - Category: [JavaScript map & geospatial visualization libraries](https://awesomedataviz.com/categories/javascript-maps/) - Website: https://canvasglobe.swiftools.com/ - Repository: https://github.com/Shree-hari/canvas-globe - License: Other - Language: JavaScript - Status: Active (commits in the last 90 days) - GitHub stars: 0 - Commits in the last 12 months: 109 - Contributors: 1 - Last commit: Sep 22, 2026 - Latest release: v1.2.0 (Sep 18, 2026) - Install (npm): `npm install canvas-globe`, 46 downloads per week - Topics: Maps & geospatial visualization ### Overview CanvasGlobe is a JavaScript mapping library. Its GitHub repository has 0 stars, 0 forks, and 1 contributor. It is actively developed with 109 commits in the last 12 months. The latest release, v1.2.0, was published on Sep 18, 2026. On npm it is downloaded about 46 times per week. ### Alternatives - [Leaflet](https://awesomedataviz.com/tools/leaflet/): JavaScript library for mobile-friendly interactive maps. (45.7K stars) - [Cesium](https://awesomedataviz.com/tools/cesium/): WebGL 3D globes and maps. (15.8K stars) - [Deck.gl](https://awesomedataviz.com/tools/deck-gl/): WebGL framework for visual exploratory data analysis of large datasets. (14.6K stars) - [OpenLayers](https://awesomedataviz.com/tools/openlayers/): Library for interactive web maps with support for many data sources, formats and projections. (12.6K stars) - [MapLibre GL JS](https://awesomedataviz.com/tools/maplibre-gl-js/): WebGL-based interactive vector tile maps in the browser; community fork of Mapbox GL JS. (11.8K stars) - [react-map-gl](https://awesomedataviz.com/tools/react-map-gl/): React components for MapLibre GL JS and Mapbox GL JS, maintained by vis.gl. (8.5K stars) Source: https://awesomedataviz.com/tools/canvasglobe/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## csvtodashboard > Turn a CSV or Excel file into an auto-built dashboard in the browser - client-side, no upload. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://csvtodashboard.com - Topics: Dashboards & BI ### Overview csvtodashboard is a data visualization app. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/csvtodashboard/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## ERD Lab > Free cloud based entity relationship diagram (ERD) tool made for developers. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://erdlab.io/ - Topics: Diagrams & diagrams as code ### Overview ERD Lab is a data visualization app. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/erd-lab/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## gnuplot > Command-line driven program for 2D and 3D plots, with many output formats. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: http://www.gnuplot.info/ - Topics: 3D & scientific visualization, Terminal & command-line charts ### Overview gnuplot is a data visualization app. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/gnuplot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Google Charts > Interactive charts for browsers and mobile devices. - Category: [JavaScript charting libraries](https://awesomedataviz.com/categories/javascript-charting-libraries/) - Website: https://developers.google.com/chart - Language: JavaScript ### Overview Google Charts is a JavaScript charting library. ### Alternatives - [Chart.js](https://awesomedataviz.com/tools/chart-js/): Charts with the canvas tag. (67.7K stars) - [Apache ECharts](https://awesomedataviz.com/tools/echarts/): Highly customizable and interactive charts ready for big datasets. (67.4K stars) - [Plotly.js](https://awesomedataviz.com/tools/plotly-js/): Powerful declarative library with support for 20 chart types. (18.4K stars) - [Lightweight Charts](https://awesomedataviz.com/tools/lightweight-charts/): Performant HTML5 canvas financial charts, from TradingView. (17.5K stars) - [ApexCharts](https://awesomedataviz.com/tools/apexcharts/): Modern & Interactive SVG Charts. (15.2K stars) - [Frappe Charts](https://awesomedataviz.com/tools/frappe-charts/): Simple, responsive SVG charts with zero dependencies. (15.1K stars) Source: https://awesomedataviz.com/tools/google-charts/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## Plotivy > Scientific data visualization tool, with AI-generated reproducible Python code, and research-oriented design best practices built in. - Category: [Data visualization apps & tools](https://awesomedataviz.com/categories/apps/) - Website: https://plotivy.app/ ### Overview Plotivy is a data visualization app. ### Alternatives - [ChartDB](https://awesomedataviz.com/tools/chartdb/): An Open-source tool to visualize database schemas and generate ER diagrams from a single query. (23K stars) - [FlameGraph](https://awesomedataviz.com/tools/flamegraph/): Stack trace visualizer that generates interactive SVG flame graphs from profiling data. (19.8K stars) - [Data Formulator](https://awesomedataviz.com/tools/data-formulator/): AI-assisted tool for transforming data and creating visualizations, from Microsoft Research. (17.5K stars) - [Sampler](https://awesomedataviz.com/tools/sampler/): Terminal dashboard that runs shell commands and visualizes their output, configured with YAML. (14.8K stars) - [QGIS](https://awesomedataviz.com/tools/qgis/): Desktop geographic information system for viewing, editing, analyzing and mapping geospatial data. (14.5K stars) - [Gource](https://awesomedataviz.com/tools/gource/): Animated visualization of software version control history. (13.2K stars) Source: https://awesomedataviz.com/tools/plotivy/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com). ## QCustomPlot > Qt C++ widget for plotting and data visualization. - Category: [C++ visualization libraries & applications](https://awesomedataviz.com/categories/cpp/) - Website: https://www.qcustomplot.com/ - Language: C++ ### Overview QCustomPlot is a C++ visualization tool. ### Alternatives - [ImPlot](https://awesomedataviz.com/tools/implot/): Immediate-mode plotting library for Dear ImGui. (6.2K stars) - [PlotJuggler](https://awesomedataviz.com/tools/plotjuggler/): Open-source Qt5 application to plot charts (based on Qwt). (6.2K stars) - [Matplot++](https://awesomedataviz.com/tools/matplotpp/): C++ graphics library for data visualization with a MATLAB-like API. (4.9K stars) - [F3D](https://awesomedataviz.com/tools/f3d/): Cross-platform, fast, and minimalist 3D viewer with scientific visualization tools. (4.7K stars) - [Mapnik](https://awesomedataviz.com/tools/mapnik/): Toolkit for rendering maps, widely used to render OpenStreetMap tiles. (4K stars) - [ROOT](https://awesomedataviz.com/tools/root/): CERN framework for analyzing, storing and visualizing large scientific datasets. (3.3K stars) Source: https://awesomedataviz.com/tools/qcustomplot/ · Data updated 2026-10-04 · Content: CC BY 4.0, Awesome Dataviz (https://awesomedataviz.com).