Metabase prioritizes ease of use with a simpler setup and intuitive UI, while Apache Superset offers deeper customization, more visualization types, and better performance at enterprise scale. Metabase wins for teams wanting quick deployment; Superset wins for organizations needing advanced analytics and visual flexibility.
Metabase vs Apache Superset — Side-by-side comparison on A Versus B
Simple, open-source BI platform with intuitive dashboard building for non-technical users.
Advanced open-source analytics platform with extensive customization and enterprise-grade scalability.
Setup Complexity. Visualization Types. Database Support. Query Performance at Scale. Learning Curve (Hours to Proficiency). Enterprise Features. Community Size (GitHub Stars)
Choose Metabase if you need a BI tool deployed in minutes with minimal infrastructure knowledge, making it ideal for small teams and startups. Choose Apache Superset if you require enterprise-grade scalability, advanced visualizations, complex data modeling, and deep customization for large organizations managing petabyte-scale data.
Metabase: 100 million | Apache Superset: 1+ billion
Metabase: Basic SQL, no templating | Apache Superset: Advanced SQL with Jinja2 templating
Metabase: $0 (open-source) or $11,940 | Apache Superset: N/A
Metabase: 1-2 weeks | Apache Superset: N/A
Metabase: 3-4 basic roles | Apache Superset: N/A
Metabase: Native iOS/Android | Apache Superset: N/A
Metabase: 2000-5000 | Apache Superset: N/A
Metabase: Basic REST API | Apache Superset: N/A
Metabase: Unlimited (self-hosted) | Apache Superset: N/A
Metabase: AGPL v3 | Apache Superset: Apache 2.0
Metabase: 0.5-2 hours | Apache Superset: 8-16 hours
Total Cost of Ownership (Year 1, 10 users)
Metabase: $3,000 (pro tier) | Apache Superset: N/A
Metabase: 20 minutes | Apache Superset: N/A
Dashboard Auto-Refresh Speed (Premium tier)
Metabase: 60,000ms (1-minute minimum) | Apache Superset: N/A
Metabase: 4 (self-hosted, Docker, cloud, hybrid) | Apache Superset: N/A
Metabase: ~2,500 enterprises | Apache Superset: N/A
Metabase: 0.5 GB (lightweight) | Apache Superset: N/A
Metabase: Basic aggregations only | Apache Superset: N/A
Base Subscription Cost (Annual, 10 Users)
Metabase: $0 (open-source) | Apache Superset: N/A
Metabase: 30+ connectors | Apache Superset: N/A
Metabase: ~15 basic functions | Apache Superset: N/A
Metabase: Basic manual roles | Apache Superset: N/A
Metabase: Full open-source self-hosting | Apache Superset: N/A
Learning Hours to Intermediate Proficiency
Metabase: 20–30 hours | Apache Superset: N/A
Metabase: ~300 MB | Apache Superset: N/A
Metabase: $120 for Professional | Apache Superset: N/A
Metabase: Yes, unlimited with self-hosting | Apache Superset: N/A
Metabase: 25+ connectors | Apache Superset: N/A
Metabase: 2-4 hours (UI-based) | Apache Superset: N/A
Metabase: $2,000-5,000 annually (self-hosted) | Apache Superset: N/A
Metabase: Premium tier only | Apache Superset: N/A
Metabase: 30,000+ | Apache Superset: N/A
Metabase: Basic dataset-level permissions | Apache Superset: N/A
Metabase: LDAP, SAML, OAuth 2.0 | Apache Superset: N/A
Metabase: 8-15 hours for basic competency | Apache Superset: N/A
Metabase: $0 (self-hosted) or $1,200 (cloud) | Apache Superset: N/A
Metabase: 25+ databases and APIs | Apache Superset: N/A
Metabase: 15-30 minutes average | Apache Superset: N/A
Metabase: No native AI features | Apache Superset: N/A
Metabase: SOC 2 Type II (managed only) | Apache Superset: N/A
Metabase: $90 (managed cloud) | Apache Superset: N/A
Metabase: Self-hosted, Docker, Kubernetes, cloud | Apache Superset: N/A
Metabase: 10-200 (startup/SMB) | Apache Superset: N/A
Metabase: 5 minutes | Apache Superset: 40 minutes
Metabase: 25+ integrations | Apache Superset: N/A
Metabase: SSPL (Elastic-style) | Apache Superset: N/A
Metabase: Basic SQL with visual query builder | Apache Superset: N/A
Metabase: 60 seconds | Apache Superset: N/A
User Interface Complexity (Learning Curve)
Metabase: 2-3 hours for dashboards | Apache Superset: N/A
Metabase: Single docker-compose command, minimal config | Apache Superset: N/A
Metabase: Basic caching (5-60 min intervals) | Apache Superset: N/A
Total Cost of Ownership (First Year, 10 Users)
Metabase: $2,900 (Pro tier) | Apache Superset: N/A
Metabase: 0.5-1 week | Apache Superset: N/A
Metabase: 40+ integrations | Apache Superset: N/A
Metabase: Basic (no native semantic layer) | Apache Superset: N/A
Metabase: Limited (via database views) | Apache Superset: N/A
Metabase: 500-2,000 users | Apache Superset: N/A
Metabase: 35,000+ | Apache Superset: 57,000+
Metabase: $3,000-10,000 | Apache Superset: N/A
Metabase: Native, no-code visual queries optional | Apache Superset: N/A
Metabase: 500-2000 | Apache Superset: N/A
Metabase: Single container, one command | Apache Superset: N/A
Metabase: 40,000+ stars | Apache Superset: N/A
Learning Curve (Days to First Dashboard)
Metabase: 0.5-1 day | Apache Superset: N/A
Metabase: 7 minutes | Apache Superset: N/A
Metabase: 25 databases | Apache Superset: N/A
Metabase: Basic query result caching | Apache Superset: N/A
Minimum Infrastructure Requirements (RAM)
Metabase: Limited (basic parameter substitution) | Apache Superset: N/A
Metabase: Full drag-and-drop support for all data sources | Apache Superset: N/A
Metabase: Email, Slack, webhooks (3 channels) | Apache Superset: N/A
Metabase: 94% successful deployment | Apache Superset: N/A
Metabase: 5 minutes | Apache Superset: 20 minutes
Metabase: 18 types | Apache Superset: 45+ types
Metabase: 30+ databases | Apache Superset: 50+ databases
Metabase: 0.5 GB | Apache Superset: 2 GB
Metabase: Not available | Apache Superset: Available
Metabase: 15-20 minutes | Apache Superset: 45-60 minutes
How to choose between Metabase and Apache Superset
Metabase vs Apache Superset — Structured Comparison Data
Machine-readable comparison dataset for Metabase vs Apache Superset. Contains 86 attribute comparisons, 5 FAQ pairs.
Metabase vs Apache Superset — Attribute Category Vocabulary
Taxonomy of attribute categories used to classify comparison data for Metabase vs Apache Superset.
Which is better for a startup with limited technical resources?
Metabase is significantly better for startups. It requires no DevOps expertise, deploys in 5 minutes via Docker or JAR file, and business users can build dashboards without SQL knowledge. Superset requires Python environment setup and ongoing infrastructure management, making it more suitable for teams with dedicated data engineering resources.
Can I use either tool for handling billions of rows of data?
Superset is purpose-built for petabyte-scale analytics with advanced caching, async query execution, and optimized database connectors. Metabase can technically connect to large datasets but experiences significant slowdowns above 100 million rows with complex joins. For billion-row datasets, Superset is the only viable choice.
What about security features like row-level security (RLS)?
Apache Superset includes RLS, full RBAC, SSO, and LDAP integration in its open-source version at no cost. Metabase lacks row-level security in open-source and requires a paid enterprise license (~$2,000+/year) for this feature. For organizations needing granular data access control, Superset is the clear winner.
How do I add custom visualizations to each platform?
Metabase offers limited customization options; custom visualizations require JavaScript modifications to core code. Superset features a robust plugin architecture allowing developers to create custom visualization components without modifying core code, making it far superior for organizations needing unique chart types.
Which has better support for modern data warehouses?
Both support Snowflake, BigQuery, and Redshift, but Superset maintains better connectors for modern data warehouses with more frequent updates and optimizations. Superset also includes native support for more specialized warehouses like Druid and Presto, while Metabase's database support is broader but sometimes lags in optimization.
How to Choose Between Metabase and Apache Superset
Setup Complexity: Metabase has Single JAR file or Docker, ~5 minutes, while Apache Superset has Requires Python environment, pip install, ~15-20 minutes.
Visualization Types: Metabase has 18 core visualization types, while Apache Superset has 45+ visualization types including custom plugins.
Database Support: Metabase has 30+ databases, while Apache Superset has 50+ databases with better connector maintenance.
Query Performance at Scale: Metabase has Good up to 100M rows; can lag with complex joins, while Apache Superset has Optimized for 1B+ rows with caching layer and async execution.
Consider: Learning Curve (Hours to Proficiency)
Learning Curve (Hours to Proficiency): Metabase has 3-5 hours for basic dashboards, while Apache Superset has 10-15 hours due to Python and customization depth.
Enterprise Features: Metabase has Basic RBAC, no row-level security in open-source, while Apache Superset has Advanced RBAC, RLS, SSO, LDAP in open-source version.
Community Size (GitHub Stars): Metabase has 35,000+ stars, while Apache Superset has 57,000+ stars.