Apache ECharts vs DataLens
| Tagline | Powerful, declarative charting library for embedding interactive visualizations | Yandex's open-source BI and data visualization system |
| Category | BI & Dashboards | BI & Dashboards |
| Replaces | Tableau, Power BI | Tableau, Power BI, Looker |
| GitHub stars | 67k | 1.7k |
| Language | TypeScript | TypeScript |
| License | Apache-2.0 | Apache-2.0 |
| Self-host difficulty | 2/5 Easy | 3/5 Moderate |
| Deploy options | Manual Docker | Docker Compose Kubernetes Manual |
| Managed hosting | ||
| Last updated | 3 days ago | 6 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
DataLens
- Ships with a limited set of connectors (ClickHouse, PostgreSQL) compared to commercial BI
- Documentation and community are smaller and partly Russian-language oriented
- Multi-service architecture makes self-hosting more involved than lightweight alternatives
- Fewer advanced governance, modeling, and enterprise integrations than Tableau/Power BI
Bottom line
Choose Apache ECharts if you want the lower-effort setup; choose Apache ECharts for the larger community and ecosystem. Apache ECharts 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