GoatCounter vs Umami
| Tagline | Easy, privacy-friendly web analytics with no tracking of personal data | 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 | 6k | 39k |
| Language | Go | TypeScript |
| License | EUPL-1.2 | MIT |
| Self-host difficulty | 2/5 Easy | 3/5 Moderate |
| Deploy options | Docker Manual | One-Click Docker Docker Compose Manual |
| Managed hosting | ||
| Last updated | 5 days 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.
GoatCounter
- Minimal by design: no funnels, cohorts, heatmaps, or session replay.
- Event/custom-property tracking is limited compared to product-analytics tools.
- Single-maintainer project, so release cadence can be slow.
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 GoatCounter 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.
GoatCounter
Easy, privacy-friendly web analytics with no tracking of personal data
Umami
Simple, fast, privacy-focused web analytics in a single lightweight dashboard