Looker vs Umami
Which no-code tool is better for your project? Compare features, pricing, and more.
Quick Verdict
Looker is best for enterprise-wide metrics governance. Umami is best for developer-friendly web analytics. Not sure? Let our AI recommend the right one.
| Feature | Looker | Umami |
|---|---|---|
| Pricing | Contact | Contact |
| Pricing Model | enterprise | freemium |
| Rating | 4.3/5 | 4.6/5 |
| AI Features | ✓ Yes | ✗ No |
| Founded | 2012 | 2020 |
| Company Size | 1000+ | 1-10 |
| Key Features |
|
|
| Integrations | BigQuery, Snowflake, Redshift, PostgreSQL | Vercel, Netlify, Docker, PostgreSQL |
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
Umami — Pros & Cons
Completely open-source (MIT license)
Free to self-host with no limits
Extremely lightweight and fast
Simple, clean interface
Very basic analytics — no funnels or advanced features
Self-hosting required for free tier
No session replays or heatmaps
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