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
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.
Pricing Model. Deployment Options. LookML Modeling Language. Data Warehouse Integration. Setup Time (days). Advanced Analytics & AI Features. User Scalability
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.
Looker: $24,000 | Metabase: $0 (open-source) or $11,940
Looker: Unlimited custom RBAC | Metabase: 3-4 basic roles
Looker: Native iOS/Android + responsive web | Metabase: Native iOS/Android
Looker: Advanced GraphQL and REST APIs | Metabase: Basic REST API
Looker: Unlimited (enterprise) | Metabase: Unlimited (self-hosted)
Looker: Excellent - Native support | Metabase: N/A
Looker: Enterprise-grade with LookML controls | Metabase: N/A
Looker: Advanced (custom dimensions, measures, derived tables) | Metabase: N/A
Looker: 1,000+ | Metabase: 30+ connectors
Looker: Native in all plans | Metabase: N/A
Looker: Field, row, and dashboard-level | Metabase: N/A
Looker: 5/10 (requires LookML expertise) | Metabase: N/A
Looker: SOC 2 Type II, ISO 27001, HIPAA, FedRAMP (GCP) | Metabase: N/A
Average Training Hours Required (Per Analyst)
Looker: Web-responsive, limited interactivity | Metabase: N/A
Looker: 9/10 (LookML code control) | Metabase: N/A
Looker: Limited predictive models | Metabase: N/A
Looker: Native SQL, complex joins, window functions | Metabase: N/A
Non-Technical User Friendliness (1-10 scale)
Looker: 5/10 (requires technical knowledge) | Metabase: N/A
Total Cost of Ownership (First Year, 10 Users)
Looker: $6,000-$12,000 (minimum enterprise license) | Metabase: $2,900 (Pro tier)
Looker: 600+ integrations | Metabase: 40+ integrations
Looker: Advanced (LookML semantic layer) | Metabase: Basic (no native semantic layer)
Looker: Native RLS with attribute-based access | Metabase: Limited (via database views)
Looker: 2-4 weeks | Metabase: 0.5-1 week
Typical Enterprise Implementation Timeline
Looker: 12 weeks average | Metabase: N/A
Looker: Full automatic caching and pushdown | Metabase: N/A
Learning Curve (Hours to First Dashboard)
Looker: 40-60 hours (with developer background) | Metabase: N/A
Looker: Purpose-built, highly white-labelable | Metabase: N/A
Looker: Native LookML ensures single source of truth | Metabase: N/A
Looker: 5,000+ users | Metabase: 500-2,000 users
Looker: Not open-source | Metabase: 40,000+ stars
Learning Curve (Days to First Dashboard)
Looker: 50+ visualizations | Metabase: N/A
Looker: 14-21 days | Metabase: 7 minutes
Looker: 9/10 (centralized LookML) | Metabase: N/A
Looker: Cloud-native SaaS (single-tenant) | Metabase: N/A
Looker: 300+ | Metabase: 25+ integrations
Looker: $3,000 per core minimum | Metabase: N/A
Looker: 8-12 weeks (requires modeling) | Metabase: N/A
Looker: Advanced (requires SQL/LookML) | Metabase: N/A
Looker: 60% of desktop features | Metabase: N/A
Looker: Built-in (LookML) - single source of truth | Metabase: N/A
Looker: Average 800ms for 100M rows | Metabase: N/A
Looker: 60+ visualization types | Metabase: N/A
Looker: LookML semantic layer with version control | Metabase: N/A
Looker: Limited; primarily desktop-focused | Metabase: N/A
Looker: 10 billion+ | Metabase: 100 million
Looker: Enterprise SDK included | Metabase: N/A
Looker: 1 (Google Cloud native) | Metabase: N/A
Looker: Basic Explore interface (code-based) | Metabase: N/A
Looker: Not available | Metabase: $0 (open-source)
Looker: Looker Studio, Einstein AI, predictive analytics | Metabase: No native ML features
Looker: LookML (proprietary) | Metabase: Query builder only (no custom language)
Looker: Closed source (Google proprietary) | Metabase: Fully open source (AGPL license)
Looker: 6-12 weeks | Metabase: 15-30 minutes average
Looker: Web-responsive design, limited mobile | Metabase: N/A
Looker: Advanced contextual RLS with LookML | Metabase: N/A
Looker: Excellent (core platform strength) | Metabase: N/A
Looker: Unrestricted (LookML + native SQL) | Metabase: N/A
Typical Mid-Market Annual Contract Value
Looker: Robust (LookML-based) | Metabase: N/A
Looker: Basic dashboards only | Metabase: N/A
Looker: Data engineers & governance | Metabase: N/A
Looker: N/A | Metabase: Basic SQL, no templating
Total Cost of Ownership (Year 1, 10 users)
Looker: N/A | Metabase: $3,000 (pro tier)
Dashboard Auto-Refresh Speed (Premium tier)
Looker: N/A | Metabase: 60,000ms (1-minute minimum)
Looker: N/A | Metabase: 4 (self-hosted, Docker, cloud, hybrid)
Looker: N/A | Metabase: ~2,500 enterprises
Looker: N/A | Metabase: 0.5 GB (lightweight)
Looker: N/A | Metabase: Basic aggregations only
Base Subscription Cost (Annual, 10 Users)
Looker: N/A | Metabase: $0 (open-source)
Looker: N/A | Metabase: ~15 basic functions
Looker: N/A | Metabase: Basic manual roles
Looker: N/A | Metabase: Full open-source self-hosting
Learning Hours to Intermediate Proficiency
Looker: N/A | Metabase: $120 for Professional
Looker: N/A | Metabase: Yes, unlimited with self-hosting
Looker: N/A | Metabase: 2-4 hours (UI-based)
Looker: N/A | Metabase: $2,000-5,000 annually (self-hosted)
Looker: N/A | Metabase: Premium tier only
Looker: N/A | Metabase: Basic dataset-level permissions
Looker: N/A | Metabase: LDAP, SAML, OAuth 2.0
Looker: N/A | Metabase: 8-15 hours for basic competency
Looker: N/A | Metabase: $0 (self-hosted) or $1,200 (cloud)
Looker: N/A | Metabase: 25+ databases and APIs
Looker: N/A | Metabase: No native AI features
Looker: N/A | Metabase: SOC 2 Type II (managed only)
Looker: N/A | Metabase: $90 (managed cloud)
Looker: N/A | Metabase: Self-hosted, Docker, Kubernetes, cloud
Looker: N/A | Metabase: 10-200 (startup/SMB)
Looker: N/A | Metabase: SSPL (Elastic-style)
Looker: N/A | Metabase: Basic SQL with visual query builder
User Interface Complexity (Learning Curve)
Looker: N/A | Metabase: 2-3 hours for dashboards
Looker: N/A | Metabase: Single docker-compose command, minimal config
Looker: N/A | Metabase: Basic caching (5-60 min intervals)
Looker: N/A | Metabase: Native, no-code visual queries optional
Looker: N/A | Metabase: Single container, one command
Looker: N/A | Metabase: Basic query result caching
Minimum Infrastructure Requirements (RAM)
Looker: N/A | Metabase: Limited (basic parameter substitution)
Looker: N/A | Metabase: Full drag-and-drop support for all data sources
Looker: N/A | Metabase: Email, Slack, webhooks (3 channels)
Looker: N/A | Metabase: 94% successful deployment
How to choose between Looker and Metabase
Looker vs Metabase — Structured Comparison Data
Machine-readable comparison dataset for Looker vs Metabase. Contains 178 attribute comparisons, 5 FAQ pairs.
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.
How to Choose Between Looker and Metabase
Pricing Model: Looker has $2,000-$5,000+ monthly (SaaS), while Metabase has $0 (self-hosted) or $1,000+ monthly (SaaS).
Deployment Options: Looker has Cloud-only (Google Cloud), while Metabase has Self-hosted, cloud, or Docker.
LookML Modeling Language: Looker has Proprietary LookML for complex transformations, while Metabase has Simple query builder, no custom language.
Data Warehouse Integration: Looker has 90+ connectors, enterprise-grade, while Metabase has 50+ connectors, adequate coverage.
Setup Time (days): Looker has 7-14 days with IT/DBA involvement, while Metabase has 1-2 days, non-technical users.
Consider: Advanced Analytics & AI Features
Advanced Analytics & AI Features: Looker has Looker Studio, Einstein AI, predictive modeling, while Metabase has Basic pivot tables, no ML-driven insights.
User Scalability: Looker has Designed for 100+ concurrent users at enterprise scale, while Metabase has Suitable for teams under 50 users.