Looker vs PostHog
Which no-code tool is better for your project? Compare features, pricing, and more.
Quick Verdict
Looker is best for enterprise-wide metrics governance. PostHog is best for product analytics for saas. Not sure? Let our AI recommend the right one.
| Feature | Looker | PostHog |
|---|---|---|
| Pricing | Contact | Contact |
| Pricing Model | enterprise | freemium |
| Rating | 4.3/5 | 4.6/5 |
| AI Features | ✓ Yes | ✓ Yes |
| Founded | 2012 | 2020 |
| Company Size | 1000+ | 50-100 |
| Key Features |
|
|
| Integrations | BigQuery, Snowflake, Redshift, PostgreSQL | Slack, Zapier, Segment, Sentry |
Looker — Pros & Cons
Best-in-class semantic layer ensures consistent metrics
Deep Google Cloud and BigQuery integration
Git-based governance is excellent for data teams
Strong embedded analytics capabilities
Enterprise pricing — expensive for small teams
LookML has a significant learning curve
Google Cloud ecosystem dependency
PostHog — Pros & Cons
All-in-one product analytics (replaces 4-5 tools)
Generous free tier (1M events/month)
Open-source and self-hostable
Built for engineers — API-first, SQL access
Can be complex to set up properly
Marketing analytics weaker than Google Analytics
Self-hosting requires infrastructure maintenance
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