Looker vs Heap

The BI platform that makes data modeling feel like a full-time job, but at least the dashboards look pretty meets automatic analytics that captures everything, so you can stop guessing what users actually do. Here's our take.

Looker

Nice Pick

The BI platform that makes data modeling feel like a full-time job, but at least the dashboards look pretty.

Pros

• Powerful LookML modeling language for reusable, version-controlled data definitions
• Seamless integration with modern data warehouses like BigQuery and Snowflake
• Self-service analytics that empowers non-technical users to build custom reports

Cons

• Steep learning curve for LookML, requiring dedicated data engineers or analysts
• Pricing can be prohibitive for small teams, with enterprise-focused costs

Heap

Automatic analytics that captures everything, so you can stop guessing what users actually do.

Pros

• Auto-captures all user events without manual instrumentation
• Retroactive analysis lets you query past data without pre-defining events
• Intuitive visual interface for non-technical team members
• Session replay and heatmaps integrated with analytics

Cons

• Can become expensive quickly as data volume grows
• Data sampling on free and lower-tier plans limits accuracy
• Requires careful data governance to avoid noise from irrelevant events

The Verdict

Use Looker if: You want powerful lookml modeling language for reusable, version-controlled data definitions and can live with steep learning curve for lookml, requiring dedicated data engineers or analysts.

Use Heap if: You prioritize auto-captures all user events without manual instrumentation over what Looker offers.

The Bottom Line

Looker wins

The BI platform that makes data modeling feel like a full-time job, but at least the dashboards look pretty.