Apache ECharts vs Kibana
| Tagline | Powerful, declarative charting library for embedding interactive visualizations | Visualize and explore Elasticsearch data with powerful BI dashboards |
| Category | BI & Dashboards | BI & Dashboards |
| Replaces | Tableau, Power BI | Tableau, Looker, Power BI |
| GitHub stars | 60k | 20k |
| Language | TypeScript | TypeScript |
| License | Apache-2.0 | Elastic-2.0 |
| Self-host difficulty | 2/5 Easy | 4/5 Involved |
| Deploy options | Manual Docker | Docker Docker Compose Kubernetes Manual |
| Managed hosting | ||
| Last updated | 1 month ago | 1 month 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
Kibana
- Tightly coupled to Elasticsearch; not useful without an ES cluster
- License changed from Apache-2.0 to Elastic-2.0 in 2021, limiting some redistributions
- Resource-heavy; full ELK stack demands significant RAM and storage
Bottom line
Choose Apache ECharts if you want the lower-effort setup; choose Apache ECharts for the larger community and ecosystem. Open each guide below for deploy steps and the full feature gap.
Apache ECharts
Powerful, declarative charting library for embedding interactive visualizations