Visualizing large datasets
Millions of points, big tables and high-dimensional data. 12 tools, ranked by GitHub stars and updated .
Tools designed for data that overwhelms ordinary chart libraries: millions of points, very large tables and high-dimensional data, using GPU rendering, aggregation or dimensionality reduction.
By GitHub stars, the most popular large-data visualization tools here are Apache ECharts (67.4K stars), Deck.gl (14.6K stars), and Kepler.gl (12K stars). 9 of 12 had commits in the last 90 days.
| 1 |
Highly customizable and interactive charts ready for big datasets. |
67.4K |
| 2 |
WebGL framework for visual exploratory data analysis of large datasets. |
14.6K |
| 3 |
Geospatial analysis tool for large-scale data sets. |
12K |
| 4 |
WebGL point cloud viewer for large datasets such as LiDAR scans. |
5.6K |
| 5 |
Large-scale WebGL-powered Geospatial Data Visualization analysis framework, maintained by Alibaba |
4.1K |
| 6 |
Renders very large datasets into accurate images by rasterizing them. |
3.6K |
| 7 |
CERN framework for analyzing, storing and visualizing large scientific datasets. |
3.3K |
| 8 |
Interactive line charts library that works with huge datasets. |
3.2K |
| 9 |
Framework for linking databases such as DuckDB with interactive views to visualize large datasets. |
1.4K |
| 10 |
Implementation of the LargeVis paper, used to visualize large-scale and high-dimensional data. |
711 |
| 11 |
Squey
Visualization software for exploring and understanding large amounts of tabular data (using parallel coordinates, timeseries and scatter plots). |
23 |
| 12 |
Open source HTML canvas treemap component supporting millions of nodes, and some functional resource usage tools, like disk and S3 usage visualization (GrandPerspective-style) |
10 |
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