Medama vs Umami
| Tagline | Privacy-focused, cookie-free website analytics in a single fast binary | Simple, fast, privacy-focused web analytics in a single lightweight dashboard |
| Category | Product & Web Analytics | Product & Web Analytics |
| Replaces | Google Analytics | Google Analytics |
| GitHub stars | 642 | 39k |
| Language | Go | TypeScript |
| License | Apache-2.0 | MIT |
| Self-host difficulty | 2/5 Easy | 3/5 Moderate |
| Deploy options | Docker Manual | One-Click Docker Docker Compose Manual |
| Managed hosting | ||
| Last updated | 1 month ago | 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.
Medama
- Bare-bones feature set: no funnels, cohorts, events depth, heatmaps, or session replay.
- Small, young project with a limited maintainer base.
- DuckDB backend is great for single-node but not built for very high-traffic multi-node scaling.
Umami
- Deliberately minimal: no heatmaps, session replay, or deep product-analytics like funnels/retention found in Mixpanel/Amplitude.
- Event/custom-property analytics are basic compared to dedicated product-analytics tools.
- No built-in alerting or anomaly detection.
Bottom line
Choose Medama if you want the lower-effort setup; choose Umami for the larger community and ecosystem. Umami has seen more recent development. Open each guide below for deploy steps and the full feature gap.
Umami
Simple, fast, privacy-focused web analytics in a single lightweight dashboard