Grafana vs Metabase
| Tagline | Observability and analytics dashboards for metrics, logs, and time series | Easy-to-use open-source BI and embedded analytics for everyone |
| Category | BI & Dashboards | BI & Dashboards |
| Replaces | Tableau, Power BI, Datadog | Tableau, Power BI, Looker |
| GitHub stars | 76k | 48k |
| Language | TypeScript | Clojure |
| License | AGPL-3.0 | AGPL-3.0 |
| Self-host difficulty | 2/5 Easy | 2/5 Easy |
| Deploy options | One-Click 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.
Grafana
- Oriented toward time-series and observability, not ad-hoc business analytics or pivot-style exploration
- No business-friendly visual query builder; dashboards assume knowledge of data sources and query languages
- Weak at relational/tabular BI reporting compared to Tableau or Power BI
- No semantic modeling layer; data modeling lives in the underlying sources
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
Both are a similar lift to self-host; choose Grafana for the larger community and ecosystem. Open each guide below for deploy steps and the full feature gap.