Looker is an enterprise-grade BI platform owned by Google with advanced modeling capabilities and higher costs ($2,000-$5,000+ monthly), while Metabase is an open-source, self-hosted alternative with lower entry costs ($0 self-hosted or $1,000+ SaaS) and simpler setup but fewer advanced features.
Looker vs Metabase — Side-by-side comparison on A Versus B
Choose Looker if you're an enterprise with complex data modeling needs, large teams, and budget for premium analytics ($30,000+ annually). Choose Metabase if you're a small-to-mid-size team wanting fast time-to-value, lower costs, and prefer open-source flexibility with self-hosting options.
Google-owned business intelligence platform built on a semantic data layer (LookML) for enterprise data governance.
Open-source BI tool with fast deployment, simple query builder, and flexible self-hosting options.
Structured comparison data for Looker vs Metabase with 178 attributes.
Average Training Hours Required (Per Analyst)
Non-Technical User Friendliness (1-10 scale)
Total Cost of Ownership (First Year, 10 Users)
Typical Enterprise Implementation Timeline
Learning Curve (Hours to First Dashboard)
Learning Curve (Days to First Dashboard)
Typical Mid-Market Annual Contract Value
Total Cost of Ownership (Year 1, 10 users)
Dashboard Auto-Refresh Speed (Premium tier)
Base Subscription Cost (Annual, 10 Users)
Learning Hours to Intermediate Proficiency
User Interface Complexity (Learning Curve)
Minimum Infrastructure Requirements (RAM)
Looker vs Metabase — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for Looker vs Metabase.
Metabase is significantly better for startups. The open-source version is completely free, deployable in minutes, and requires no specialized data engineering. Looker's $2,000+ monthly starting price and complex setup make it impractical for early-stage companies. Metabase allows startups to get analytics running in 1-2 days vs. 7-14 days for Looker.
Only Metabase supports self-hosting. You can deploy it on your own servers, Docker, AWS, or any cloud infrastructure. Looker is cloud-only and runs exclusively on Google Cloud, which limits flexibility for organizations with strict on-premise requirements or existing cloud providers.
Which has better data modeling capabilities?
Looker's LookML language is far more powerful for complex data transformations and reusable business logic. It allows data engineers to build sophisticated semantic layers. Metabase's query builder is simpler and faster for basic queries but lacks the flexibility to handle complex modeling scenarios that large enterprises require.
How do the two platforms handle scaling?
Looker is built for enterprise scale, supporting 100+ concurrent users with enterprise-grade performance and governance. Metabase self-hosted becomes challenging beyond 50 concurrent users; for larger teams, the paid SaaS version ($1,000+/month) is recommended, though it still lacks Looker's advanced features at scale.
Does either platform include AI or predictive analytics?
Looker includes Einstein AI integration (Google's AI suite) for predictive analytics, anomaly detection, and automated insights. Metabase has no native ML or AI features. If predictive modeling or AI-driven insights are core requirements, Looker is the only viable choice, though it comes at significantly higher cost.