uPlot

📈 μPlot

A small (~35 KB min), fast chart for time series, lines, areas, ohlc & bars (MIT Licensed)


Introduction

μPlot is a fast, memory-efficient Canvas 2D-based chart for plotting time series, lines, areas, ohlc & bars; from a cold start it can create an interactive chart containing 150,000 data points in 135ms, scaling linearly at ~25,000 pts/ms. In addition to fast initial render, the zooming and cursor performance is by far the best of any similar charting lib; at ~35 KB, it’s likely the smallest and fastest time series plotter that doesn’t make use of context-limited WebGL shaders or WASM, both of which have much higher startup cost and code size.

166,650 point bench: https://leeoniya.github.io/uPlot/bench/uPlot.html

However, if you need 60fps performance with massive streaming datasets, uPlot can only get you so far. WebGL should still be the tool of choice for applications like realtime signal or waveform visualizations: See danchitnis/webgl-plot, huww98/TimeChart, epezent/implot, or commercial products like LightningChart®.


uPlot Chart


Features


Non-Features

In order to stay lean, fast and focused the following features will not be added:


Documentation (WIP)

The docs are a perpetual work in progress, it seems. Start with /docs/README.md for a conceptual overview. The full API is further documented via comments in /dist/uPlot.d.ts. Additionally, an ever-expanding collection of runnable /demos covers the vast majority of uPlot’s API.


Third-party Integrations


Performance

Benchmarks done on this hardware:

uPlot Performance

Full size: https://leeoniya.github.io/uPlot/demos/multi-bars.html

Raw data: https://github.com/leeoniya/uPlot/blob/master/bench/results.json

| lib                    | size    | done    | js,rend,paint,sys | heap peak,final | mousemove (10s)     |
| ---------------------- | ------- | ------- | ----------------- | --------------- | ------------------- |
| uPlot v1.6.9           |   39 KB |   58 ms |   70   1   1   38 |  20 MB   3 MB   |   65  159   88  103 |
| ECharts v5.1.0         |  987 KB |   88 ms |   87   1   1   47 |  55 MB   5 MB   | 1463  284   84  521 |
| Chart.js v3.2.0        |  233 KB |   80 ms |  118   1   1   41 |  34 MB  11 MB   |  725   30   57 1467 |
| Flot v3.0.0            |  494 KB |   91 ms |  118   3   1   55 |  46 MB  16 MB   | ---                 |
| LightningChart® v2.2.1 | 1000 KB |  --- ms |  178   2   1   42 |  61 MB  22 MB   | 5310   46   43  180 |
| dygraphs v2.1.0        |  125 KB |  135 ms |  159   2   1   75 |  99 MB  44 MB   | 1087  162   74  205 |
| CanvasJS v3.2.13       |  482 KB |  241 ms |  271   2   1   66 |  52 MB  26 MB   |  961  256   76  195 |
| Highcharts v9.0.1      |  391 KB |  --- ms |  286   4   2   42 | 108 MB  33 MB   |  840  301  132  155 |
| dvxCharts v5.0.0       |  369 KB |  253 ms |  310  18   1   51 |  60 MB  24 MB   |  674  442  148  145 |
| Plotly.js v1.58.4      | 3500 KB |  377 ms |  408   5   1   71 | 199 MB  46 MB   | 1087  114   29   82 |
| Chart.js v2.9.4        |  245 KB |  495 ms |  524   2   1   75 | 103 MB  54 MB   | 8397    5    6 1158 |
| ECharts v4.9.0         |  785 KB |  366 ms |  498   1   1  581 | 224 MB  78 MB   | 2265   64   17 7551 |
| ApexCharts v3.26.1     |  478 KB |  --- ms | 1634  22   1   44 | 332 MB  70 MB   | 8611  646   99  154 |
| ZingChart v2.9.3       |  857 KB | 2081 ms | 2101   5   1   38 | 191 MB 100 MB   | ---                 |
| amCharts v4.10.18      | 1200 KB | 5564 ms | 4925  19   6   67 | 695 MB 237 MB   | 1494  336  164  285 |

Normally, all libs are updated to their latest versions before each benchmark round. However, libraries which show significant performance improvements in latest versions will have prior versions shown to encourage migration; this is especially true for still-widely-deployed libs, such as Chart.js v2.9.4, and ECharts v4.9.0. Deployment prevalence is assessed from public npm and CDN download stats for the prior few months.

Some libraries provide their own performance demos:

TODO (all of these use SVG, so performance should be similar to Highcharts):


Acknowledgements