Metabase vs Rill
| Tagline | Easy-to-use open-source BI and embedded analytics for everyone | Fast operational BI with embedded OLAP for interactive dashboards |
| Category | BI & Dashboards | BI & Dashboards |
| Replaces | Tableau, Power BI, Looker | Tableau, Looker, Power BI |
| GitHub stars | 49k | 2.9k |
| Language | Clojure | Go |
| License | AGPL-3.0 | Apache-2.0 |
| Self-host difficulty | 2/5 Easy | 3/5 Moderate |
| Deploy options | One-Click Docker Docker Compose Kubernetes Manual | Docker Manual Kubernetes |
| Managed hosting | ||
| Last updated | yesterday | yesterday |
| View repo | View repo |
Where each falls short
The honest trade-offs — what you give up with each, versus the proprietary tools they replace.
Metabase
- Advanced data modeling, row-level security, and SSO are gated behind the paid Pro/Enterprise editions
- Charting and visualization depth is more limited than Tableau or Power BI
- No deep semantic modeling layer like Looker's LookML
- Performance can degrade on very large datasets without careful tuning or caching
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 Metabase if you want the lower-effort setup; choose Metabase for the larger community and ecosystem. Open each guide below for deploy steps and the full feature gap.