PostHog vs Prisme Analytics
| Tagline | All-in-one product analytics, session replay, feature flags, and A/B testing | Event-stream analytics built on ClickHouse for developer teams |
| Category | Product & Web Analytics | Product & Web Analytics |
| Replaces | Mixpanel, Amplitude, Hotjar, Google Analytics | Google Analytics, Mixpanel, Amplitude |
| GitHub stars | 35k | 430 |
| Language | Python | Go |
| License | MIT | AGPL-3.0 |
| Self-host difficulty | 5/5 Advanced | 3/5 Moderate |
| Deploy options | Docker Compose Kubernetes Manual | Docker Docker Compose |
| Managed hosting | ||
| Last updated | 5 days ago | 1 month 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.
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.
Prisme Analytics
- No no-code dashboard builder; requires SQL knowledge for custom reports
- ClickHouse dependency increases minimum infrastructure footprint
- No session replay, heatmaps, or A/B testing modules
Bottom line
Choose Prisme Analytics 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