plotly (R) vs Shiny
A data-driven comparison of two R data visualization packages: popularity, development activity, licensing and installation. Updated .
plotly (R)Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams
ShinyFramework for creating interactive applications/visualisations
Key differences
- Shiny has 2.1× as many GitHub stars as plotly (R) (5.7K vs 2.7K).
- Shiny had more development activity over the last 12 months: 63 commits vs 19.
- Shiny is downloaded 3.2× as often on CRAN (192.4K vs 59.9K per week).
- Both are released under the MIT license.
- Shiny is the older project: its repository was created in 2012, plotly (R)'s in 2013.
By the numbers
- plotly (R)
- Shiny
Show data as a table
| Metric | plotly (R) | Shiny |
|---|---|---|
| GitHub stars | 2,682 | 5,694 |
| CRAN downloads / week | 59,895 | 192,447 |
| Commits, last 12 months | 19 | 63 |
| Contributors | 57 | 92 |
| Forks | 640 | 1,891 |
Development activity
Commits per month to each default branch, last 12 complete months.
- plotly (R)
- Shiny
Show data as a table
| Month | plotly (R) | Shiny |
|---|---|---|
| Oct 2025 | 0 | 5 |
| Nov 2025 | 0 | 4 |
| Dec 2025 | 0 | 13 |
| Jan 2026 | 13 | 3 |
| Feb 2026 | 0 | 7 |
| Mar 2026 | 0 | 0 |
| Apr 2026 | 3 | 5 |
| May 2026 | 0 | 9 |
| Jun 2026 | 1 | 6 |
| Jul 2026 | 2 | 6 |
| Aug 2026 | 0 | 5 |
| Sep 2026 | 0 | 0 |
Side by side
| Attribute | plotly (R) | Shiny |
|---|---|---|
| Description | Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams | Framework for creating interactive applications/visualisations |
| Category | R data visualization packages | R data visualization packages |
| License | MIT | MIT |
| Language | R | R |
| Status | Active | Active |
| Latest release | v4.12.1 () | v1.14.0 () |
| Last commit | ||
| Repository created | ||
| Open issues | 715 | 796 |
| Install | install.packages("plotly") | install.packages("shiny")npm install @posit/shiny |
Which should you choose?
Popularity and activity are only part of the story. Consider which ecosystem you work in, the chart types and interactions you need, how much data you render, and whether the license fits your project. Both tool pages list alternatives if neither is quite right.
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plotly (R)
Interactive charts (including adding interactivity to ggplot2 output), cartograms and simple network diagrams
-
Shiny
Framework for creating interactive applications/visualisations