Counter vs PostHog
| Tagline | Minimalist self-hosted hit counter and page-view tracker | All-in-one product analytics, session replay, feature flags, and A/B testing |
| Category | Product & Web Analytics | Product & Web Analytics |
| Replaces | Google Analytics, Hotjar | Mixpanel, Amplitude, Hotjar, Google Analytics |
| GitHub stars | 2k | 35k |
| Language | Go | Python |
| License | MIT | MIT |
| Self-host difficulty | 1/5 Effortless | 5/5 Advanced |
| Deploy options | One-Click Docker Manual | Docker Compose Kubernetes Manual |
| Managed hosting | ||
| Last updated | 1 month ago | 5 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.
Counter
- No funnel, cohort, or retention analysis whatsoever
- No custom event tracking beyond page hits
- Data aggregation is coarse; no drill-down by browser, OS, or campaign
PostHog
- Self-hosting the full ClickHouse + Kafka + Postgres + Redis stack is heavy; the project actively steers smaller users toward PostHog Cloud.
- Some enterprise features live under a separate proprietary
eelicense, not pure MIT. - The all-in-one breadth means it is more complex to operate than a focused tool like Mixpanel.
Bottom line
Choose Counter if you want the lower-effort setup; choose PostHog for the larger community and ecosystem. PostHog has seen more recent development. Open each guide below for deploy steps and the full feature gap.
PostHog
All-in-one product analytics, session replay, feature flags, and A/B testing