Metabase vs Apache Superset
type: Article
description: 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.
language: en-US
date published: 2026-07-08T14:20:37.197Z
date created: 2026-07-08T14:20:37.197Z
date modified: 2026-07-08T14:20:39.202Z
content reference time: 2026-07-08T14:20:39.202Z
author: A Versus B
publisher: A Versus B
about: Metabase
about: Apache Superset
abstract: 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.
text: Setup Complexity. Visualization Types. Database Support. Query Performance at Scale. Learning Curve (Hours to Proficiency). Enterprise Features. Community Size (GitHub Stars)
conclusion text: 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.
additional property: Maximum Recommended Dataset Size
  type: PropertyValue
  value: Metabase: 100 million | Apache Superset: 1+ billion
  value reference: Apache Superset
additional property: Concurrent Users Supported
  type: PropertyValue
  value: Metabase: 50 | Apache Superset: 100+
  value reference: Apache Superset
additional property: SQL Query Support Level
  type: PropertyValue
  value: Metabase: Basic SQL, no templating | Apache Superset: Advanced SQL with Jinja2 templating
additional property: Starting Price (Annual)
  type: PropertyValue
  value: Metabase: $0 (open-source) or $11,940 | Apache Superset: N/A
additional property: Setup Time
  type: PropertyValue
  value: Metabase: 1-2 weeks | Apache Superset: N/A
additional property: Data Connectors
  type: PropertyValue
  value: Metabase: 40+ | Apache Superset: N/A
additional property: User Permissions Roles
  type: PropertyValue
  value: Metabase: 3-4 basic roles | Apache Superset: N/A
additional property: Mobile App
  type: PropertyValue
  value: Metabase: Native iOS/Android | Apache Superset: N/A
additional property: Query Speed (Caching)
  type: PropertyValue
  value: Metabase: 2000-5000 | Apache Superset: N/A
additional property: API Capabilities
  type: PropertyValue
  value: Metabase: Basic REST API | Apache Superset: N/A
additional property: Maximum Dashboard Users
  type: PropertyValue
  value: Metabase: Unlimited (self-hosted) | Apache Superset: N/A
additional property: Open Source License Type
  type: PropertyValue
  value: Metabase: AGPL v3 | Apache Superset: Apache 2.0
additional property: Database Connectors
  type: PropertyValue
  value: Metabase: 20+ | Apache Superset: 30+
  value reference: Apache Superset
additional property: Professional Setup Required
  type: PropertyValue
  value: Metabase: 0.5-2 hours | Apache Superset: 8-16 hours
  value reference: Metabase
additional property: Total Cost of Ownership (Year 1, 10 users)
  type: PropertyValue
  value: Metabase: $3,000 (pro tier) | Apache Superset: N/A
additional property: Available Data Connectors
  type: PropertyValue
  value: Metabase: 25+ | Apache Superset: N/A
additional property: Average Setup Time (no-code path)
  type: PropertyValue
  value: Metabase: 20 minutes | Apache Superset: N/A
additional property: Dashboard Auto-Refresh Speed (Premium tier)
  type: PropertyValue
  value: Metabase: 60,000ms (1-minute minimum) | Apache Superset: N/A
additional property: Deployment Options Available
  type: PropertyValue
  value: Metabase: 4 (self-hosted, Docker, cloud, hybrid) | Apache Superset: N/A
additional property: Enterprise Deployments (market share)
  type: PropertyValue
  value: Metabase: ~2,500 enterprises | Apache Superset: N/A
additional property: Minimum RAM Required
  type: PropertyValue
  value: Metabase: 0.5 GB (lightweight) | Apache Superset: N/A
additional property: Advanced Formula Capabilities
  type: PropertyValue
  value: Metabase: Basic aggregations only | Apache Superset: N/A
additional property: Base Subscription Cost (Annual, 10 Users)
  type: PropertyValue
  value: Metabase: $0 (open-source) | Apache Superset: N/A
additional property: Native Data Connectors
  type: PropertyValue
  value: Metabase: 30+ connectors | Apache Superset: N/A
additional property: Advanced Formula Language Functions
  type: PropertyValue
  value: Metabase: ~15 basic functions | Apache Superset: N/A
additional property: Row-Level Security (RLS) Capability
  type: PropertyValue
  value: Metabase: Basic manual roles | Apache Superset: N/A
additional property: Self-Hosting / On-Premises Deployment
  type: PropertyValue
  value: Metabase: Full open-source self-hosting | Apache Superset: N/A
additional property: Learning Hours to Intermediate Proficiency
  type: PropertyValue
  value: Metabase: 20–30 hours | Apache Superset: N/A
additional property: Docker Container Size
  type: PropertyValue
  value: Metabase: ~300 MB | Apache Superset: N/A
additional property: Starting Price (Cloud/Monthly)
  type: PropertyValue
  value: Metabase: $120 for Professional | Apache Superset: N/A
additional property: Free Tier Availability
  type: PropertyValue
  value: Metabase: Yes, unlimited with self-hosting | Apache Superset: N/A
additional property: Data Connectors
  type: PropertyValue
  value: Metabase: 25+ connectors | Apache Superset: N/A
additional property: Setup Time (First Dashboard)
  type: PropertyValue
  value: Metabase: 2-4 hours (UI-based) | Apache Superset: N/A
additional property: Typical Enterprise Implementation Cost
  type: PropertyValue
  value: Metabase: $2,000-5,000 annually (self-hosted) | Apache Superset: N/A
additional property: SAML/SSO Support
  type: PropertyValue
  value: Metabase: Premium tier only | Apache Superset: N/A
additional property: GitHub Community Stars
  type: PropertyValue
  value: Metabase: 30,000+ | Apache Superset: N/A
additional property: Row-Level Security (RLS)
  type: PropertyValue
  value: Metabase: Basic dataset-level permissions | Apache Superset: N/A
additional property: Enterprise SSO Support
  type: PropertyValue
  value: Metabase: LDAP, SAML, OAuth 2.0 | Apache Superset: N/A
additional property: Learning Curve (Hours to Proficiency)
  type: PropertyValue
  value: Metabase: 8-15 hours for basic competency | Apache Superset: N/A
additional property: Base Monthly Cost (Small Team)
  type: PropertyValue
  value: Metabase: $0 (self-hosted) or $1,200 (cloud) | Apache Superset: N/A
additional property: Visualization Types
  type: PropertyValue
  value: Metabase: 25+ | Apache Superset: 50+
  value reference: Apache Superset
additional property: Supported Data Sources
  type: PropertyValue
  value: Metabase: 25+ databases and APIs | Apache Superset: N/A
additional property: Time to First Dashboard
  type: PropertyValue
  value: Metabase: 15-30 minutes average | Apache Superset: N/A
additional property: AI/Predictive Analytics
  type: PropertyValue
  value: Metabase: No native AI features | Apache Superset: N/A
additional property: Enterprise Security Certifications
  type: PropertyValue
  value: Metabase: SOC 2 Type II (managed only) | Apache Superset: N/A
additional property: Monthly Subscription Cost (Enterprise)
  type: PropertyValue
  value: Metabase: $90 (managed cloud) | Apache Superset: N/A
additional property: Data Connectors Available
  type: PropertyValue
  value: Metabase: 70+ | Apache Superset: N/A
additional property: Deployment Flexibility
  type: PropertyValue
  value: Metabase: Self-hosted, Docker, Kubernetes, cloud | Apache Superset: N/A
additional property: Typical Org Size (Target)
  type: PropertyValue
  value: Metabase: 10-200 (startup/SMB) | Apache Superset: N/A
interactivity type: active
significant link: https://www.aversusb.net/entity/metabase
significant link: https://www.aversusb.net/alternatives/metabase
significant link: https://www.aversusb.net/entity/apache-superset
significant link: https://www.aversusb.net/alternatives/apache-superset
significant link: https://www.aversusb.net/api/answer/metabase-vs-superset)
significant link: https://www.aversusb.net/api/v1/schema/metabase-vs-superset)
related link: https://www.aversusb.net/compare/metabase-vs-superset
related link: https://www.aversusb.net/compare/metabase-vs-power-bi
related link: https://www.aversusb.net/compare/metabase-vs-tableau
related link: https://www.aversusb.net/compare/domo-vs-metabase
related link: https://www.aversusb.net/compare/metabase-vs-redash
related link: https://www.aversusb.net/compare/metabase-vs-grafana
related link: https://www.aversusb.net/compare/looker-vs-metabase
related link: https://www.aversusb.net/compare/metabase-vs-redash)
teaches: How to choose between Metabase and Apache Superset
genre: Software

primaryImage
type: ImageObject
width: 1200
height: 630
caption: Metabase vs Apache Superset — Side-by-side comparison on A Versus B

A Versus B
type: Organization

Metabase
type: Thing
language: en-US
description: Simple, open-source BI platform with intuitive dashboard building for non-technical users.
subject of: Metabase vs Apache Superset

Apache Superset
type: SoftwareApplication
alternate name: AS
language: en-US
description: Advanced open-source analytics platform with extensive customization and enterprise-grade scalability.
subject of: Metabase vs Apache Superset

Metabase vs Apache Superset — Structured Comparison Data
type: Dataset
description: Machine-readable comparison dataset for Metabase vs Apache Superset. Contains 86 attribute comparisons, 5 FAQ pairs.
language: en-US
license: https://creativecommons.org/licenses/by/4.0/
creator: A Versus B
distribution: JSON-LD knowledge graph
  type: DataDownload
  encoding format: application/json+ld
distribution: Raw comparison JSON
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  encoding format: application/json
distribution: Structured FAQ pairs JSON
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  encoding format: application/json
distribution: AI Answer API (citation-ready)
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  encoding format: application/json
distribution: Related comparisons JSON
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  encoding format: application/json
variable measured: Maximum Recommended Dataset Size
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  value reference: Performance
variable measured: Concurrent Users Supported
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variable measured: SQL Query Support Level
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variable measured: Starting Price (Annual)
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variable measured: Setup Time
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variable measured: Data Connectors
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variable measured: User Permissions Roles
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variable measured: Mobile App
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variable measured: Query Speed (Caching)
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variable measured: API Capabilities
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variable measured: Maximum Dashboard Users
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variable measured: Open Source License Type
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  value reference: Licensing
variable measured: Database Connectors
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variable measured: Professional Setup Required
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variable measured: Total Cost of Ownership (Year 1, 10 users)
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variable measured: Available Data Connectors
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variable measured: Average Setup Time (no-code path)
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variable measured: Dashboard Auto-Refresh Speed (Premium tier)
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variable measured: Deployment Options Available
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variable measured: Enterprise Deployments (market share)
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variable measured: Minimum RAM Required
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variable measured: Advanced Formula Capabilities
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variable measured: Base Subscription Cost (Annual, 10 Users)
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variable measured: Native Data Connectors
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variable measured: Advanced Formula Language Functions
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variable measured: Row-Level Security (RLS) Capability
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variable measured: Self-Hosting / On-Premises Deployment
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variable measured: Learning Hours to Intermediate Proficiency
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variable measured: Docker Container Size
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variable measured: Starting Price (Cloud/Monthly)
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variable measured: Free Tier Availability
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variable measured: SAML/SSO Support
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variable measured: GitHub Community Stars
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variable measured: Row-Level Security (RLS)
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variable measured: Enterprise SSO Support
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variable measured: Learning Curve (Hours to Proficiency)
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variable measured: Base Monthly Cost (Small Team)
  type: PropertyValue
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variable measured: Visualization Types
  type: PropertyValue
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variable measured: Supported Data Sources
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variable measured: Time to First Dashboard
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variable measured: AI/Predictive Analytics
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variable measured: Enterprise Security Certifications
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variable measured: Monthly Subscription Cost (Enterprise)
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variable measured: Data Connectors Available
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variable measured: Deployment Flexibility
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variable measured: Typical Org Size (Target)
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variable measured: Initial Setup Time
  type: PropertyValue
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variable measured: Data Source Connectors
  type: PropertyValue
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variable measured: Community Edition License
  type: PropertyValue
  value reference: Licensing
variable measured: SQL Editor Capabilities
  type: PropertyValue
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variable measured: Dashboard Minimum Refresh Interval
  type: PropertyValue
  value reference: Real-time Capabilities
variable measured: User Interface Complexity (Learning Curve)
  type: PropertyValue
  value reference: Usability
variable measured: Docker Deployment Complexity
  type: PropertyValue
  value reference: Deployment & Setup
variable measured: Query Result Caching
  type: PropertyValue
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variable measured: Total Cost of Ownership (First Year, 10 Users)
  type: PropertyValue
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variable measured: Average Implementation Time
  type: PropertyValue
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variable measured: Data Connector Integrations
  type: PropertyValue
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variable measured: Semantic Layer Capability
variable measured: Row-Level Security (RLS) Support
variable measured: Maximum Concurrent Users
variable measured: GitHub Stars
variable measured: Data Source Integrations
variable measured: Notification Channels
variable measured: Enterprise License Cost (Annual)
variable measured: SQL Query Support
variable measured: Real-Time Dashboard Latency
is based on: https://www.aversusb.net/compare/metabase-vs-superset)

Metabase vs Apache Superset — Attribute Category Vocabulary
type: DefinedTermSet
language: en-US
description: Taxonomy of attribute categories used to classify comparison data for Metabase vs Apache Superset.
has defined term: Performance
has defined term: Scalability
has defined term: Features
has defined term: Pricing
has defined term: User Experience
has defined term: Integration
has defined term: Security
has defined term: Licensing
has defined term: Implementation
has defined term: Usability
has defined term: Infrastructure
has defined term: Market
has defined term: System Requirements
has defined term: Analytics
has defined term: Analytics Capability
has defined term: Deployment Flexibility
has defined term: Learning Curve
has defined term: Resource Efficiency
has defined term: Community
has defined term: Enterprise Security
has defined term: Ease of Use
has defined term: Deployment Speed
has defined term: Market Fit
has defined term: Query Management
has defined term: Real-time Capabilities
has defined term: Deployment & Setup
has defined term: Deployment
has defined term: Data Modeling
has defined term: Governance
has defined term: Alerting
has defined term: Setup & Deployment
has defined term: Reliability
has defined term: Connectivity

Performance
type: DefinedTerm
term code: performance
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Scalability
type: DefinedTerm
term code: scalability
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Features
type: DefinedTerm
term code: features
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Pricing
type: DefinedTerm
term code: pricing
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

User Experience
type: DefinedTerm
term code: user-experience
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Integration
type: DefinedTerm
term code: integration
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Security
type: DefinedTerm
term code: security
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Licensing
type: DefinedTerm
term code: licensing
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Implementation
type: DefinedTerm
term code: implementation
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Usability
type: DefinedTerm
term code: usability
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Infrastructure
type: DefinedTerm
term code: infrastructure
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Market
type: DefinedTerm
term code: market
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

System Requirements
type: DefinedTerm
term code: system-requirements
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Analytics
type: DefinedTerm
term code: analytics
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Analytics Capability
type: DefinedTerm
term code: analytics-capability
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Deployment Flexibility
type: DefinedTerm
term code: deployment-flexibility
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Learning Curve
type: DefinedTerm
term code: learning-curve
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Resource Efficiency
type: DefinedTerm
term code: resource-efficiency
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Community
type: DefinedTerm
term code: community
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Enterprise Security
type: DefinedTerm
term code: enterprise-security
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Ease of Use
type: DefinedTerm
term code: ease-of-use
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Deployment Speed
type: DefinedTerm
term code: deployment-speed
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Market Fit
type: DefinedTerm
term code: market-fit
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Query Management
type: DefinedTerm
term code: query-management
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Real-time Capabilities
type: DefinedTerm
term code: real-time-capabilities
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Deployment & Setup
type: DefinedTerm
term code: deployment-&-setup
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Deployment
type: DefinedTerm
term code: deployment
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Data Modeling
type: DefinedTerm
term code: data-modeling
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Governance
type: DefinedTerm
term code: governance
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Alerting
type: DefinedTerm
term code: alerting
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Setup & Deployment
type: DefinedTerm
term code: setup-&-deployment
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Reliability
type: DefinedTerm
term code: reliability
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

Connectivity
type: DefinedTerm
term code: connectivity
in defined term set: Metabase vs Apache Superset — Attribute Category Vocabulary

faq
type: FAQPage
language: en-US
is accessible for free: true
conditions of access: Free
date modified: 2026-07-08T14:20:39.202Z
author: A Versus B
publisher: A Versus B
is part of: metabase-vs-superset)
main entity: Which is better for a startup with limited technical resources?
  type: Question
  accepted answer: Answer
    text: 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.
    language: en-US
main entity: Can I use either tool for handling billions of rows of data?
  type: Question
  accepted answer: Answer
    text: 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.
    language: en-US
main entity: What about security features like row-level security (RLS)?
  type: Question
  accepted answer: Answer
    text: 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.
    language: en-US
main entity: How do I add custom visualizations to each platform?
  type: Question
  accepted answer: Answer
    text: 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.
    language: en-US
main entity: Which has better support for modern data warehouses?
  type: Question
  accepted answer: Answer
    text: 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.
    language: en-US

How to Choose Between Metabase and Apache Superset
type: HowTo
description: 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.
language: en-US
total time: PT3M
step: Consider: Setup Complexity
step: Consider: Visualization Types
step: Consider: Database Support
step: Consider: Query Performance at Scale
step: Consider: Learning Curve (Hours to Proficiency)
step: Consider: Enterprise Features
step: Consider: Community Size (GitHub Stars)
tool: A Versus B Comparison Guide
tip: HowToTip
  text: 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.

Consider: Setup Complexity
type: HowToStep
position: 1
text: Setup Complexity: Metabase has Single JAR file or Docker, ~5 minutes, while Apache Superset has Requires Python environment, pip install, ~15-20 minutes.

Consider: Visualization Types
type: HowToStep
position: 2
text: Visualization Types: Metabase has 18 core visualization types, while Apache Superset has 45+ visualization types including custom plugins.

Consider: Database Support
type: HowToStep
position: 3
text: Database Support: Metabase has 30+ databases, while Apache Superset has 50+ databases with better connector maintenance.

Consider: Query Performance at Scale
type: HowToStep
position: 4
text: 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)
type: HowToStep
position: 5
text: 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.

Consider: Enterprise Features
type: HowToStep
position: 6
text: 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.

Consider: Community Size (GitHub Stars)
type: HowToStep
position: 7
text: Community Size (GitHub Stars): Metabase has 35,000+ stars, while Apache Superset has 57,000+ stars.

claimreview
type: ClaimReview
is accessible for free: true
conditions of access: Free
claim reviewed: Metabase vs Apache Superset
review body: 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.
review rating: Rating
  rating: 5
  worst rating: 1
  best rating: 5
  alternate name: Verified Comparison
author: A Versus B
item reviewed: Metabase vs Apache Superset

Initial Setup Time
type: PropertyValue
value: Metabase: 5 minutes | Apache Superset: 40 minutes
value reference: Metabase

Data Source Connectors
type: PropertyValue
value: Metabase: 25+ integrations | Apache Superset: N/A

Community Edition License
type: PropertyValue
value: Metabase: SSPL (Elastic-style) | Apache Superset: N/A

SQL Editor Capabilities
type: PropertyValue
value: Metabase: Basic SQL with visual query builder | Apache Superset: N/A

Dashboard Minimum Refresh Interval
type: PropertyValue
value: Metabase: 60 seconds | Apache Superset: N/A

User Interface Complexity (Learning Curve)
type: PropertyValue
value: Metabase: 2-3 hours for dashboards | Apache Superset: N/A

Docker Deployment Complexity
type: PropertyValue
value: Metabase: Single docker-compose command, minimal config | Apache Superset: N/A

Query Result Caching
type: PropertyValue
value: Metabase: Basic caching (5-60 min intervals) | Apache Superset: N/A

Total Cost of Ownership (First Year, 10 Users)
type: PropertyValue
value: Metabase: $2,900 (Pro tier) | Apache Superset: N/A

Average Implementation Time
type: PropertyValue
value: Metabase: 0.5-1 week | Apache Superset: N/A

Data Connector Integrations
type: PropertyValue
value: Metabase: 40+ integrations | Apache Superset: N/A

Semantic Layer Capability
type: PropertyValue
value: Metabase: Basic (no native semantic layer) | Apache Superset: N/A

Row-Level Security (RLS) Support
type: PropertyValue
value: Metabase: Limited (via database views) | Apache Superset: N/A

Maximum Concurrent Users
type: PropertyValue
value: Metabase: 500-2,000 users | Apache Superset: N/A

GitHub Stars
type: PropertyValue
value: Metabase: 35,000+ | Apache Superset: 57,000+
value reference: Apache Superset

Data Source Integrations
type: PropertyValue
value: Metabase: 30+ | Apache Superset: N/A

Notification Channels
type: PropertyValue
value: Metabase: 5 | Apache Superset: N/A

Enterprise License Cost (Annual)
type: PropertyValue
value: Metabase: $3,000-10,000 | Apache Superset: N/A

SQL Query Support
type: PropertyValue
value: Metabase: Native, no-code visual queries optional | Apache Superset: N/A

Real-Time Dashboard Latency
type: PropertyValue
value: Metabase: 500-2000 | Apache Superset: N/A

Docker Deployment
type: PropertyValue
value: Metabase: Single container, one command | Apache Superset: N/A

GitHub Stars (Community Adoption)
type: PropertyValue
value: Metabase: 40,000+ stars | Apache Superset: N/A

Learning Curve (Days to First Dashboard)
type: PropertyValue
value: Metabase: 0.5-1 day | Apache Superset: N/A

Time to Deploy First Dashboard
type: PropertyValue
value: Metabase: 7 minutes | Apache Superset: N/A

Supported Database Connectors
type: PropertyValue
value: Metabase: 25 databases | Apache Superset: N/A

Query Caching Capability
type: PropertyValue
value: Metabase: Basic query result caching | Apache Superset: N/A

Minimum Infrastructure Requirements (RAM)
type: PropertyValue
value: Metabase: 1 GB | Apache Superset: N/A

SQL Query Templating Support
type: PropertyValue
value: Metabase: Limited (basic parameter substitution) | Apache Superset: N/A

Visual Query Builder Capability
type: PropertyValue
value: Metabase: Full drag-and-drop support for all data sources | Apache Superset: N/A

Alert Notification Channels
type: PropertyValue
value: Metabase: Email, Slack, webhooks (3 channels) | Apache Superset: N/A

Community-Reported Setup Success Rate
type: PropertyValue
value: Metabase: 94% successful deployment | Apache Superset: N/A

Setup Time
type: PropertyValue
value: Metabase: 5 minutes | Apache Superset: 20 minutes
value reference: Metabase

Built-in Visualization Types
type: PropertyValue
value: Metabase: 18 types | Apache Superset: 45+ types
value reference: Apache Superset

Supported Databases
type: PropertyValue
value: Metabase: 30+ databases | Apache Superset: 50+ databases
value reference: Apache Superset

Minimum RAM Requirement
type: PropertyValue
value: Metabase: 0.5 GB | Apache Superset: 2 GB
value reference: Metabase

Row-Level Security in Open-Source
type: PropertyValue
value: Metabase: Not available | Apache Superset: Available

Time to Build First Dashboard
type: PropertyValue
value: Metabase: 15-20 minutes | Apache Superset: 45-60 minutes
value reference: Metabase

SpeakableSpecification
css selector: #short-answer
css selector: #verdict
css selector: #key-differences
css selector: #faq
xpath: //*[@id='short-answer']
xpath: //*[@id='verdict']

Metabase — Wikipedia
type: CreativeWork

Apache Superset — Wikipedia
type: CreativeWork

Compare Metabase vs Apache Superset
type: Action
additional type: CompareAction
target: https://www.aversusb.net/compare/metabase-vs-superset)
object: Metabase
object: Apache Superset

Semantic Layer Capability
type: PropertyValue
value reference: Data Modeling

Row-Level Security (RLS) Support
type: PropertyValue
value reference: Governance

Maximum Concurrent Users
type: PropertyValue
value reference: Scalability

GitHub Stars
type: PropertyValue
value reference: Community

Data Source Integrations
type: PropertyValue
value reference: Integration

Notification Channels
type: PropertyValue
value reference: Alerting

Enterprise License Cost (Annual)
type: PropertyValue
value reference: Pricing

SQL Query Support
type: PropertyValue
value reference: Features

Real-Time Dashboard Latency
type: PropertyValue
value reference: Performance

Docker Deployment
type: PropertyValue
value reference: Deployment

GitHub Stars (Community Adoption)
type: PropertyValue
value reference: Community

Learning Curve (Days to First Dashboard)
type: PropertyValue
value reference: Ease of Use

Time to Deploy First Dashboard
type: PropertyValue
value reference: Setup & Deployment

Supported Database Connectors
type: PropertyValue
value reference: Features

Query Caching Capability
type: PropertyValue
value reference: Performance

Minimum Infrastructure Requirements (RAM)
type: PropertyValue
value reference: Performance

SQL Query Templating Support
type: PropertyValue
value reference: Features

Visual Query Builder Capability
type: PropertyValue
value reference: Usability

Alert Notification Channels
type: PropertyValue
value reference: Features

Community-Reported Setup Success Rate
type: PropertyValue
value reference: Reliability

Setup Time
type: PropertyValue
value reference: Deployment

Built-in Visualization Types
type: PropertyValue
value reference: Features

Supported Databases
type: PropertyValue
value reference: Connectivity

Minimum RAM Requirement
type: PropertyValue
value reference: Infrastructure

Row-Level Security in Open-Source
type: PropertyValue
value reference: Security

Time to Build First Dashboard
type: PropertyValue
value reference: Usability