Apache Superset vs Metabase
| Tagline | Enterprise-ready BI web app for data exploration and dashboards | Easy-to-use open-source BI and embedded analytics for everyone |
| Category | BI & Dashboards | BI & Dashboards |
| Replaces | Tableau, Looker, Power BI | Tableau, Power BI, Looker |
| GitHub stars | 74k | 48k |
| Language | TypeScript | Clojure |
| License | Apache-2.0 | AGPL-3.0 |
| Self-host difficulty | 3/5 Moderate | 2/5 Easy |
| Deploy options | Docker Docker Compose Kubernetes Manual | One-Click Docker Docker Compose Kubernetes Manual |
| Managed hosting | ||
| Last updated | 2 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 Superset
- No native desktop authoring app like Tableau Desktop; all work happens in the browser
- Visualization customization is less polished and flexible than Tableau's drag-and-drop canvas
- No built-in semantic/modeling layer comparable to Looker's LookML (relies on external tools)
- Steeper learning curve and heavier infrastructure (Celery, Redis, metadata DB) for production
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
Bottom line
Choose Metabase if you want the lower-effort setup; choose Apache Superset for the larger community and ecosystem. Open each guide below for deploy steps and the full feature gap.