Apache ECharts vs Rill
| Tagline | Powerful, declarative charting library for embedding interactive visualizations | Fast operational BI with embedded OLAP for interactive dashboards |
| Category | BI & Dashboards | BI & Dashboards |
| Replaces | Tableau, Power BI | Tableau, Looker, Power BI |
| GitHub stars | 67k | 2.8k |
| Language | TypeScript | Go |
| License | Apache-2.0 | Apache-2.0 |
| Self-host difficulty | 2/5 Easy | 3/5 Moderate |
| Deploy options | Manual Docker | Docker Manual Kubernetes |
| Managed hosting | ||
| Last updated | 3 days ago | 2 days ago |
| View repo | View repo |
Where each falls short
The honest trade-offs — what you give up with each, versus the proprietary tools they replace.
Apache ECharts
- Library only; no built-in query layer or data connector UI
- Requires custom development to build a full dashboard application
- No user management or saved-dashboard persistence out of the box
Rill
- Narrower visualization set than Tableau/Power BI, focused on time-series and metrics dashboards
- Dashboards are defined in code/YAML, less approachable for non-technical authors
- Smaller connector ecosystem; centered on OLAP engines like DuckDB and ClickHouse
- Younger project with a smaller community and fewer enterprise governance features
Bottom line
Choose Apache ECharts if you want the lower-effort setup; choose Apache ECharts for the larger community and ecosystem. Rill has seen more recent development. Open each guide below for deploy steps and the full feature gap.
Apache ECharts
Powerful, declarative charting library for embedding interactive visualizations