Apache ECharts vs Dashy
| Tagline | Powerful, declarative charting library for embedding interactive visualizations | Feature-rich homelab homepage with easy YAML configuration and a polished UI |
| Category | BI & Dashboards | BI & Dashboards |
| Replaces | Tableau, Power BI | Tableau, Looker, Power BI |
| GitHub stars | 67k | 26k |
| Language | TypeScript | Nodejs |
| License | Apache-2.0 | MIT |
| Self-host difficulty | 2/5 Easy | 2/5 Easy |
| Deploy options | Manual Docker | Docker Docker Compose Manual |
| Managed hosting | ||
| Last updated | 6 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
Dashy
- No analytical data visualization, BI queries, or database connectivity
- Multi-user support is basic; no proper RBAC or team workspaces
- Service auto-discovery requires manual YAML entries; no Docker auto-detection like Homepage
- Not suitable for business reporting or data-driven dashboards
Bottom line
Both are a similar lift to self-host; 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
Dashy
Feature-rich homelab homepage with easy YAML configuration and a polished UI