Druid vs Umami
| Tagline | Distributed, column-oriented real-time analytics data store for high-throughput queries | Simple, fast, privacy-focused web analytics in a single lightweight dashboard |
| Category | Product & Web Analytics | Product & Web Analytics |
| Replaces | Google Analytics, Mixpanel, Amplitude | Google Analytics |
| GitHub stars | 14k | 37k |
| Language | Java | TypeScript |
| License | Apache-2.0 | MIT |
| Self-host difficulty | 5/5 Advanced | 3/5 Moderate |
| Deploy options | Docker Docker Compose Kubernetes Manual | One-Click Docker Docker Compose Manual |
| 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.
Druid
- No built-in session analytics, funnel analysis, or retention cohorts compared to Mixpanel/Amplitude
- Requires significant infrastructure knowledge (ZooKeeper, deep-storage, coordinator/broker/historical nodes)
- No out-of-the-box user-facing dashboarding — must pair with Superset or Grafana
- Operational cost and cluster management overhead is very high for small teams
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 Umami if you want the lower-effort setup; choose Umami for the larger community and ecosystem. Open each guide below for deploy steps and the full feature gap.