For most developers, browser charting works fine — until it doesn’t. Once you push beyond tens of thousands of points, add live streaming, or need advanced interactions, the story changes: frame drops, frozen dashboards, memory issues.
That’s where SciChart’s JavaScript Chart Library comes in. The new v4 release expanded GPU acceleration for real-time streaming, meaning our library offers one of the fastest JavaScript chart solutions. v4 also introduced specialized chart types such as polar and radar plots, plus arc heatmaps. Built by developers for developers, it’s designed to handle the problems that break other libraries.
Fastest JavaScript Chart Library Performance Benchmarks
The platform is powered by WebAssembly + GPU acceleration, ensuring heavy rendering never blocks the JS thread.
- 100 charts with 10M points in a drag-and-drop dashboard at ~60 FPS → React drag-and-drop demo
- Big-data stress test pushing browser limits to 100M data-points → Big data stress test
- Performance tests vs. Chart.js, Highcharts, and Plotly.js show why this data visualisation tool consistently outperforms alternatives → Performance comparison of the fastest JavaScript chart libraries
And speed isn’t just a bragging right. In finance, aerospace, or medical dashboards, slow charts mean missed signals. That’s why the platform is engineered not just to render faster than alternatives, but to stay smooth and reliable under sustained load.
It also bypasses WebGL context limits, so you can run hundreds of charts and thousands of series on a single page without browser crashes.
Quick Start with Working Templates
The package ships with ready-to-run templates for React, Angular, Vue, and plain JS.
npm install scichart
That’s it - no signup, no sales call required. From there, customise with TypeScript + IntelliSense, backed by hundreds of live demos and working boilerplates.
Real-Time Streaming
Static data is easy; streaming is where many libraries struggle. Rolling buffers and GPU batching let developers subscribe to a WebSocket or MQTT feed and keep the UI responsive - even under sustained load.
// Example: append live WebSocket data to a SciChart surfacesocket.
onmessage = (msg) => {
const data = JSON.parse(msg.data);
// Access the renderable series from the chart, e.g. line, column, scatter
const renderSeries = sciChartSurface.renderableSeries.get(0);
// Access the associated data series
const dataSeries = renderSeries.dataSeries;
// Append your data, SciChart.js expects number[] or Float64Array values
// The chart will automatically update, and redraw, re-scale
dataSeries.appendRange(data.xValues, data.yValues);
};
That’s why the data visualisation tool is deployed in domains where real-time is non-negotiable: trading platforms, MedTech telemetry, industrial monitoring.
Interactivity Without Overhead
Zooming, panning, and cursors are built in. More complex behaviour — like syncing multiple charts or restricting zoom to a modifier key — is a config option, not a weekend project. This flexibility means you can build sophisticated dashboards without reinventing the basics.
Advanced Chart Types (70+)
Beyond the usual line and bar charts, the library includes 70+ chart types, covering both common and specialist needs:
- 2D: Line, Spline, Step, Mountain/Area, Bar/Column, Stacked, Scatter, Bubble, Candlestick, OHLC, Band, Pie/Donut, Waterfall, Error Bars, Impulse.
- Specialised: Polar and Radar charts; Heatmaps (incl. Arc Heatmaps), Contour/Isolines, Vector fields, Triangle/Polygon series.
- 3D: Surface meshes, Point clouds, 3D columns/bubbles.
- UI & Data Viz Extras: Gauges, Treemaps, Geo-maps.
Explore live examples: arc heatmap, interactive waterfall, 3D surface mesh. Browse the full JS demo gallery. Browse the full React demo gallery.
What Can You Build?
Here are some representative JavaScript demos you can run and inspect:
- Realtime audio / RF analysers: Interactive waterfall
- Server traffic monitoring: Server traffic dashboard
- Medical devices (ECG & Ultrasound): ECG vital signs, Polar heatmap ultrasound
- Financial trading: Realtime stock charts, Depth chart
- Oil & gas exploration: Drill-depth dashboard
- Scientific visualisation: Heatmap interactions
These are just examples - the library is also used in aerospace, defense, geoscience, and other industries where visualisation must perform at scale.
Dashboards That Don’t Break Overnight
If you’ve ever left a browser dashboard running overnight only to find it frozen in the morning, you know the pain.
The data visualisation tool was designed for long-running applications:
- 24/7 monitoring dashboards
- Medical telemetry systems
- Aerospace & defence mission controls
- Financial trading platforms
Production dashboards have been seen running continuously for weeks without a restart. Memory leaks aren’t optional fixes; they’re deal-breakers. This tool won’t stop you from writing leaky code, but it gives you the visibility to track and resolve issues before they hit production.
Developer Experience That Scales
Teams stick with this library because the API bends to your use case — time-series telemetry, scientific overlays, or custom modifiers:
- Deep customisation: axes, ticks, gridlines, cursors, tooltips, legends, rendering order
- Unlimited axes: linear, logarithmic, date, category — stacked, centered, or aligned
- Per-point customisation: dynamic styling via PaletteProvider
- Overlay control: shapes, annotations, regions, or custom HTML/SVG — even thousands of draggable/editable annotations without lag
- Events that matter: hover callbacks, selection events, hit-testing, linked zoom/pan
Learning is supported by:
- 400+ live demos (React, Angular, Vanilla JS) editable in CodeSandbox/StackBlitz
- Docs and samples that work (not placeholders)
- TypeScript-first API with IntelliSense
- A built-in GPT assistant for instant answers while coding
- Direct engineer support from the core team, with rapid fixes and updates
Open Source vs Commercial JavaScript Chart Library
If you’re plotting fewer than ~10k points in a simple dashboard that isn’t expected to grow — and no one is going to ask “can we add this custom interaction?” or “make it all dynamic?” — open-source libraries like Chart.js, D3, or Plotly are a perfectly good choice.
But once requirements shift to millions of points, 24/7 uptime, specialised chart types, or deep custom interactions, those tools usually hit their ceiling. At that point, teams either spend months hacking around the gaps — or switch to a commercial data visualisation tool that has already solved them.
And it’s not just about data size. Teams in pharma, life sciences, and industrial R&D often deal with modest datasets but still need precise labelling, custom annotations, drill-downs, and compliance-grade reliability — areas where generic OSS charting struggles.
Why Choosing the Fastest JavaScript Chart Library Matters
Dashboards aren’t just visuals — they’re decision-making tools. Whether you’re building in finance, MedTech, aerospace, or trying to wrangle a firehose of data, your charts have to keep up — and be maintainable when stakeholders inevitably ask for the next customisation.
SciChart’s JavaScript Chart Library includes a free Community Edition for non-commercial, educational, and personal use - available on https://www.npmjs.com/package/scichart or (LINK: https://www.scichart.com/getting-started/scichart-javascript/).
Curious what others think? Hundreds of developers and teams have shared detailed reviews on Reviews.io, G2, and Capterra — useful if you want to hear from people running this data visualisation tool in production.