Looker (Google) vs Heap
Side-by-side comparison to help you choose the best tool.
Looker (Google)
paidGoogle's enterprise BI platform with AI data exploration, semantic modelling, and Looker AI features for natural language data analysis. Looker uses LookML, a proprietary modelling language that creates a single source of truth for business metrics across the organisation. Its integration with Google Cloud and Vertex AI enables sophisticated machine learning workflows directly within the BI environment.
Heap
freemiumHeap is an automatic product analytics platform that captures every user interaction - clicks, taps, swipes, form submissions - without requiring manual event tracking. Its AI Heap Illuminate feature proactively discovers friction points and conversion opportunities hidden in your data, so teams can fix problems they didn't know to look for.
| Feature | Looker (Google) | Heap |
|---|---|---|
| Pricing | paid | freemium |
| Category | Data & Analytics | Data & Analytics |
| Rating | 4.5 | 4.4 |
| Best For | Enterprise teams on Google Cloud needing governed, embedded analytics | Product teams who want complete behavioural data capture without engineering overhead |
| Views | 6 | 4 |
Pros
- Strong semantic layer for consistent metrics
- Excellent Google Cloud integration
- Powerful embedded analytics options
Cons
- LookML requires developer expertise
- Premium pricing limits smaller teams
Pros
- No manual event tagging needed
- Retroactive analysis of historical data
- AI surfaces insights automatically
Cons
- Can generate very large data volumes
- Pricing not transparent for larger plans
- LookML semantic modelling layer
- Natural language data exploration
- Google Cloud and BigQuery native integration
- Embedded analytics capabilities
- Centralised metric governance
- Automatic event capture
- AI-powered Heap Illuminate
- Retroactive data analysis
- Session replay integration
- Journey maps