A complete sample — not an excerpt. Members comparing any 2–5 tools get this exact format.

The ask: pick a charting library for a company dashboard. React + TypeScript team; charts must stay smooth on low-end office laptops and export cleanly into weekly-deck slides.

echarts vs Chart.js vs plotly.js

2026/11/2 12:16:51 生成 · 共 3 个工具

These three are not the same layer. ECharts is a chart engine: the widest chart coverage and the steadiest at scale, at the cost of bundle size and config verbosity. Chart.js is a lightweight canvas: fastest to start and smallest, but complex interactions are on you. plotly.js is scientific visualisation: best 3D and statistical plots, but its default look is academic and needs restyling inside an enterprise dashboard. Pick ECharts for dashboards, Chart.js for marketing-page mini charts, plotly.js for analysis tools.

Top pick:Apache ECharts

An enterprise dashboard needs three things: broad chart coverage, no stutter at scale, and export. ECharts ships 20+ chart types (maps, sankey, graph), renders to canvas so tens of thousands of points stay interactive, and its built-in toolbox exports images in one click — exactly the 'put it in a deck' requirement. The cost is a verbose first integration.

Side by side

Dimension	echarts	Chart.js	plotly.js
Positioning	Full chart engine	Lightweight basics	Scientific / statistical
Bundle size (gzip, rough)	Large; tree-shakeable	Very small	Largest
Chart types	20+, incl. maps / graph / sankey	8 basic types	Best at statistics + 3D
At scale	Canvas; 10k+ points interactive	Stable in the thousands	Moderate; 3D is heavy
React integration	No official wrapper; mature community ones	react-chartjs-2, officially maintained	react-plotly.js, community
Image export	Built-in toolbox	Via canvas.toDataURL	Built-in modebar
Styling	Highly configurable	Simple and direct	Academic default look
Learning curve	Medium; many options	Low	Medium-high
Ecosystem	67.6k ★, best Chinese docs	67.8k ★, best English docs	18.4k ★, common in research
License	Apache-2.0	MIT	MIT

Which one for which scenario

Internal dashboard: many chart types, export into a weekly report
20+ types cover most dashboard needs, and the toolbox exports PNG without you writing an exporter.
Marketing landing page with two or three mini charts, first-paint speed first
Smallest bundle, officially maintained React wrapper, a few dozen lines to a chart. Not worth 200KB on this kind of page.
Analysis tool needing 3D scatter, box plots, zoomable axes
Statistical and 3D charts are its home turf; the other two need workarounds here.
Vue-only team that also needs China map visualisation
Mature Vue wrappers and built-in map support; the others need an external map data source.

Strengths and weaknesses

echarts

Details

Full chart engine — the dashboard default

Widest coverage: maps, sankey, graph, radar all built in
Canvas rendering keeps 10k+ points interactive on weak hardware
Toolbox: PNG export, data view, area zoom
Richest Chinese docs and examples; lowest troubleshooting cost for CN teams
Verbose options — even a simple chart needs a long config
No official React wrapper; you rely on community ones
Default theme is 'big screen'; restyle it for clean admin UIs

Chart.js

Details

Lightweight basics, fastest to start

Small and direct — a chart in a few dozen lines
Officially maintained React wrapper, no surprises
MIT — no commercial concerns
Only 8 basic types; maps and graphs need another library
Complex interactions (linked highlight, large-data zoom) are DIY
Less steady than canvas engines at scale

plotly.js

Details

Scientific and statistical visualisation

Best 3D scatter, contour and box plots
Modebar: zoom, box-select, image export
Same lineage as Python plotly — cheap for data teams
Largest bundle — wrong choice for speed-sensitive pages
Academic default look; restyle for enterprise dashboards
Community React wrapper, slower to track releases