Blazing Fast Performance
Render 10M+ data points at 60 FPS using native WebGL. No canvas limitations, no performance bottlenecks.
SciChart EngineUltra-fast WebGL Scientific Charts
Render millions of points at 60 FPS with WebGL-powered precision
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Interactive Demo
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Quick Start
Installation
bash
npm install scichart-engine
# or
pnpm add scichart-engineBasic Usage
typescript
import { createChart } from 'scichart-engine'
const chart = createChart({
container: document.getElementById('chart'),
xAxis: { label: 'Time', auto: true },
yAxis: { label: 'Value', auto: true },
})
// Add data
chart.addSeries({
id: 'my-series',
type: 'line',
data: {
x: new Float32Array([0, 1, 2, 3, 4]),
y: new Float32Array([0, 1, 4, 9, 16]),
},
style: { color: '#00f2ff' },
})React Usage
tsx
import { SciChart } from 'scichart-engine/react'
function MyChart() {
const series = [{
id: 'data',
x: new Float32Array([0, 1, 2, 3, 4]),
y: new Float32Array([0, 1, 4, 9, 16]),
color: '#00f2ff',
}]
return (
<SciChart
series={series}
xAxis={{ label: 'Time', auto: true }}
yAxis={{ label: 'Value', auto: true }}
height="400px"
/>
)
}Why SciChart Engine?
| Feature | SciChart Engine | Chart.js | Plotly |
|---|---|---|---|
| Max Points (60 FPS) | 10M+ | ~10k | ~100k |
| Rendering | WebGL | Canvas 2D | SVG/WebGL |
| Bundle Size | ~50KB | ~200KB | ~3MB |
| TypedArray Support | ✅ Native | ❌ | Partial |
| React Support | ✅ First-class | Plugin | ✅ |
| Real-time Streaming | ✅ Optimized | ⚠️ Limited | ⚠️ Limited |
Use Cases
- Scientific Research - Visualize experimental data with millions of measurements
- Financial Data - High-frequency trading charts with real-time updates
- IoT & Sensors - Stream and display sensor data in real-time
- Signal Processing - Analyze waveforms, spectrograms, and time-series data
- Medical Devices - ECG, EEG, and other biomedical signal visualization
- Industrial Monitoring - Process control and equipment monitoring dashboards