Decision comparison
Metabase vs Apache Superset
Metabase and Apache Superset both document dashboards, SQL capabilities, semantic-layer concepts, and open-source availability, but our research supports a feature-and-buying comparison rather than a universal winner. Metabase documents a visual query builder alongside a SQL editor, interactive dashboards, drill-through, subscriptions, alerts, a governed semantic layer, APIs, an MCP server, and embedded analytics tooling. Its public plan page lists a free Open Source option; Starter at $100 per month ($1,080 per year); Pro at $575 per month ($6,210 per year); and custom-priced Enterprise. Starter includes the first 5 users and Pro includes the first 10 users, with additional-user charges stated separately. Metabase also offers a 14-day trial for Starter and Pro. Apache Superset documents a no-code visualization builder, SQL IDE, REST API, physical and virtual datasets, SQL semantic-layer transformations, 40+ pre-installed visualization types, Jinja templating, dashboard filters, and a plug-in architecture. Its official site identifies it as open source but lists no paid plan or public price. Buyers should assess the documented interfaces, extension model, deployment responsibilities, and the exact Metabase plan terms required for their intended use.
Direct comparison. These are reviewed substitutes bought for the same job, so the differences below are the ones that decide between them.
All 2 are BI platforms.
Quick Comparison
| Decision factor | Metabase | Apache Superset |
|---|---|---|
| Ease of Use | Visual query builder for queries without SQL, plus a SQL editor for complex analysis. | No-code visualization builder is documented alongside a SQL IDE; our research does not support a general ease-of-use ranking. |
| Visualization Library | Interactive dashboards and visualizations are documented; no chart-type count is documented. | 40+ pre-installed visualization types, including detailed geospatial charts, plus a plug-in architecture for custom visualizations. |
| Query Approach | Visual query builder, SQL editor, and AI-assisted plain-English data questions through Metabot. | No-code visualization building and custom SQL through the SQL IDE, with database metadata browsing and Jinja templating. |
| Deployment Options | Self-hosted or Metabase Cloud; Cloud handles setup, backups, and upgrades. Enterprise can offer air-gapped deployment for an additional fee. | Administrator documentation covers installation, configuration, security, and database drivers; no managed offering is established by Superset's documentation. |
| Pricing Model | Community Edition is free, open-source and self-hosted, with unlimited users. Paid Metabase Cloud plans start with Starter at $100/month, or $90/month billed annually, including the first 5 users, then $6 per user/month. Pro is $575/month, or $517.50/month annually, including the first 10 users, then $12 per user/month. Enterprise is custom pricing starting at $20,000/year. Both paid plans offer a 14 days free trial. | Free and open-source under Apache License 2.0 |
| Best For | Teams seeking the documented combination of visual and SQL querying, governed semantic-layer curation, interactive dashboards, and embedded analytics components. | Teams whose requirements align with documented SQL tools, REST API access, physical and virtual datasets, semantic-layer SQL transformations, and visualization plug-ins. |
Metabase
- Ease of Use:
- Visual query builder for queries without SQL, plus a SQL editor for complex analysis.
- Visualization Library:
- Interactive dashboards and visualizations are documented; no chart-type count is documented.
- Query Approach:
- Visual query builder, SQL editor, and AI-assisted plain-English data questions through Metabot.
- Deployment Options:
- Self-hosted or Metabase Cloud; Cloud handles setup, backups, and upgrades. Enterprise can offer air-gapped deployment for an additional fee.
- Pricing Model:
- Community Edition is free, open-source and self-hosted, with unlimited users. Paid Metabase Cloud plans start with Starter at $100/month, or $90/month billed annually, including the first 5 users, then $6 per user/month. Pro is $575/month, or $517.50/month annually, including the first 10 users, then $12 per user/month. Enterprise is custom pricing starting at $20,000/year. Both paid plans offer a 14 days free trial.
- Best For:
- Teams seeking the documented combination of visual and SQL querying, governed semantic-layer curation, interactive dashboards, and embedded analytics components.
Apache Superset
- Ease of Use:
- No-code visualization builder is documented alongside a SQL IDE; our research does not support a general ease-of-use ranking.
- Visualization Library:
- 40+ pre-installed visualization types, including detailed geospatial charts, plus a plug-in architecture for custom visualizations.
- Query Approach:
- No-code visualization building and custom SQL through the SQL IDE, with database metadata browsing and Jinja templating.
- Deployment Options:
- Administrator documentation covers installation, configuration, security, and database drivers; no managed offering is established by Superset's documentation.
- Pricing Model:
- Free and open-source under Apache License 2.0
- Best For:
- Teams whose requirements align with documented SQL tools, REST API access, physical and virtual datasets, semantic-layer SQL transformations, and visualization plug-ins.
Public signals
Verified factual signals only. Bars appear only for like-for-like metrics with five weekly assessments for every tool; missing evidence stays explicit. These signals do not establish enterprise adoption, product quality, or total cost.
| Metric | Metabase | Apache Superset |
|---|---|---|
| Docker Hub pulls(Product adoption) | 279.2M | 608.9M |
| GitHub commits, 90d(Product adoption) | 2.3k | 2.2k |
| GitHub stars(Product adoption) | 50,000+ | 75,000+ |
| Search interest(Market interest) | 1 | 1 |
| Hacker News mentions, 90d(Community interest) | 11 | 0 |
| npm weekly downloads(Developer adoption) | 80.6k | 12.7k |
| Product Hunt comments(Community interest) | 30 | 0 |
| Product Hunt rating(Community interest) | 4.9/5 | Unavailable |
| Product Hunt reviews(Community interest) | 24 | 0 |
| Product Hunt votes(Community interest) | 314 | 69 |
| Stack Overflow questions(Community interest) | 374 | 1.3k |
| PyPI weekly downloads(Product adoption) | Not available | 106.5k |
As of November 9, 2026 — updated weekly.
Health & risk evidence
Observed public-source checks for mapped package versions and repositories.
Metabase
November 9, 2026Package vulnerabilities
npm · @metabase/embedding-sdk-react@0.65.2
0 vulnerabilities
across 1 package
Repository security score
github.com/metabase/metabase
7.1/10
Apache Superset
November 9, 2026Package vulnerabilities
npm · @superset-ui/core@0.20.4 · PyPI · apache-superset@6.1.0
0 vulnerabilities
across 2 packages
Repository security score
github.com/apache/superset
5.5/10
Interface Preview
Metabase
Apache Superset
Feature Comparison
| Feature | Metabase | Apache Superset |
|---|---|---|
| Data Exploration | ||
| Visual Query Builder | Visual query builder for querying without SQL; SQL editor is also available for complex analysis. | No-code visualization builder; SQL IDE for exploration with custom SQL queries. |
| SQL Tools | SQL editor plus models and metrics for recurring questions and calculations. | SQL Lab supports custom SQL, database metadata browsing, and Jinja templating. |
| Drill-Through & Filtering | Drill-through on charts plus interactive dashboard filters and breakouts. | Dashboard filters, cross-filters, drill-to-detail, and drill-by are documented. |
| Visualization & Dashboards | ||
| Visualization Types | Superset's documentation documents charts, visualizations, and interactive dashboards; it does not list a supported chart-type count. | 40+ pre-installed visualization types, including detailed geospatial charts; custom visualizations can be built through plug-ins. |
| Dashboard Features | Interactive dashboards, subscriptions, alerts, and Documents that combine charts with text are documented. | Dashboards, dashboard filters, CSS templates, and feature flags are documented. |
| Caching | Caching controls are listed on Pro. | Data caching for chart and dashboard load time is documented. |
| Embedded Analytics | ||
| Embedding Options | Embedded dashboards and visualizations, self-service reporting, and an SDK for advanced setups are documented. | Not available: Superset's documentation does not establish an embedding option or SDK. |
| Multi-Tenant Controls | Pro lists multi-tenant embedded analytics and data segregation including row- and column-level security and granular permissions. | Not available: Superset's documentation does not establish multi-tenant controls. |
| Brand Customization | Pro lists brand customization and white-label readiness; the product site documents dynamic styling. | CSS templates for customizing charts and dashboards to a brand’s look and feel. |
| Security & Governance | ||
| Access Control | Table-, row-, and column-level access limits; granular permissions; and role-based visibility are documented. | The Superset site directs administrators to security documentation but does not list equivalent access-control details. |
| Authentication | Pro lists SSO, required 2FA, and IP allowlists; the product site lists SAML, LDAP, JWT, and Google integrations. | Not available: Superset's documentation does not identify supported authentication providers. |
| Usage Analytics | Usage analytics and auditing are listed on Pro; the product site describes tracking content, data access, and downloads. | Not available: Superset's documentation does not establish usage-analytics functionality. |
| Architecture & Extensibility | ||
| Data Sources | 20+ supported data sources are listed on the pricing page. | Connects to SQL-based databases, including cloud-native databases and engines at petabyte scale; Superset's documentation does not list a connector count. |
| Semantic Layer | A governed semantic layer of canonical tables and metrics is documented; Data Studio supports trusted reusable metrics and vetted data sources. | Semantic layer for SQL data transformations; physical and virtual datasets are documented. |
| API & Extensions | APIs, CLI, MCP server, Slack integration, and an SDK for advanced embedded setups are documented. | REST API and a plug-in architecture for custom visualizations are documented. |
Data Exploration
Visual Query Builder
SQL Tools
Drill-Through & Filtering
Visualization & Dashboards
Visualization Types
Dashboard Features
Caching
Embedded Analytics
Embedding Options
Multi-Tenant Controls
Brand Customization
Security & Governance
Access Control
Authentication
Usage Analytics
Architecture & Extensibility
Data Sources
Semantic Layer
API & Extensions
Which to choose
Metabase and Apache Superset both document dashboards, SQL capabilities, semantic-layer concepts, and open-source availability, but our research supports a feature-and-buying comparison rather than a universal winner. Metabase documents a visual query builder alongside a SQL editor, interactive dashboards, drill-through, subscriptions, alerts, a governed semantic layer, APIs, an MCP server, and embedded analytics tooling. Its public plan page lists a free Open Source option; Starter at $100 per month ($1,080 per year); Pro at $575 per month ($6,210 per year); and custom-priced Enterprise. Starter includes the first 5 users and Pro includes the first 10 users, with additional-user charges stated separately. Metabase also offers a 14-day trial for Starter and Pro. Apache Superset documents a no-code visualization builder, SQL IDE, REST API, physical and virtual datasets, SQL semantic-layer transformations, 40+ pre-installed visualization types, Jinja templating, dashboard filters, and a plug-in architecture. Its official site identifies it as open source but lists no paid plan or public price. Buyers should assess the documented interfaces, extension model, deployment responsibilities, and the exact Metabase plan terms required for their intended use.
Best-fit scenarios
Choose Metabase if:
Choose Metabase when the documented combination of visual querying, SQL editing, interactive dashboards, semantic-layer curation, and embedded analytics components matches the work you need to support. Metabase documents plain-English data questions through Metabot AI, APIs and an MCP server for working with data and tools, and an SDK for advanced embedded setups. For commercial evaluation, confirm the deployment choice and applicable plan: the Open Source plan is listed as free with unlimited users, questions, and dashboards; Starter is listed at $100 per month or $1,080 per year; Pro is listed at $575 per month or $6,210 per year; and Enterprise is custom priced. Starter has 5 included users and Pro has 10 included users, while both internal analytics users and embed users count as users. Confirm additional-user charges, taxes, optional usage-based features, and whether Enterprise-only air-gapped deployment, procurement support, a dedicated success engineer, or the 1-day support SLA is relevant.
Choose Apache Superset if:
Choose Apache Superset when its documented open-source visualization and exploration stack matches your requirements: a no-code visualization builder, SQL IDE, REST API, physical and virtual datasets, semantic-layer SQL transformations, 40+ pre-installed visualization types, and custom visualization development through a plug-in architecture. Its administrator documentation scope includes installation, configuration, security, and database drivers. Evaluate whether these documented tools, plus dashboard filters, Jinja templating, data caching, CSS templates, and feature flags, meet your implementation needs.
These scenarios reflect the available product evidence. Your requirements, existing stack, and team expertise should guide the final decision.
Frequently Asked Questions
What is the documented difference between Metabase and Apache Superset?
Both products document dashboards and SQL-oriented exploration, but their public product descriptions emphasize different capabilities. Metabase documents a visual query builder, a SQL editor, interactive dashboards, a governed semantic layer of canonical tables and metrics, and plain-English questions through Metabot AI. Its site also lists APIs, an MCP server, CLI access, Slack, embedded dashboards, and an SDK for advanced embedded setups. Apache Superset describes an open-source data exploration and visualization platform with a no-code visualization builder, a SQL IDE, dashboards, physical and virtual datasets, a REST API, and a semantic layer for SQL data transformations. Superset also documents 40+ pre-installed visualization types and a plug-in architecture for custom visualizations.
Is Apache Superset free compared with Metabase?
The Apache Superset website identifies Superset as an open-source platform, but it does not list a paid-plan or public-price schedule. Metabase’s official pricing page lists an Open Source plan as Free, with unlimited users, questions, and dashboards. It also lists Starter at $100 per month or $1,080 per year, plus $6 per user per month after the first 5 included users; Pro at $575 per month or $6,210 per year, plus $12 per user per month after the first 10 included users; and Enterprise with custom pricing. Prices exclude applicable taxes. Metabase states that a 14-day trial is available for Starter and Pro. A like-for-like managed-service price comparison is not supported by Superset's public documentation.
What does the public documentation show about embedded analytics?
Metabase documents embedded dashboards, visualizations, and self-service reporting. It says teams can begin with simple charts or full dashboards and use its SDK for advanced setups. Metabase's pricing page says Pro includes unlimited embedded charts and dashboards with tailored interactivity, customer AI questions, multi-tenant data segregation including row- and column-level security and granular permissions, and brand customization. The product site also documents dynamic styling and interactive controls ranging from view-only to full data discovery. Apache Superset's documentation covers dashboards, chart building, SQL tools, datasets, a REST API, and a visualization plug-in architecture, but it does not establish a comparable Superset embedding SDK or commercial embedding package.
Which documented query and visualization tools are available?
Metabase documents a visual query builder for creating queries without SQL and a SQL editor for more complex analysis. It also documents drill-through interactions, dashboard filtering and breakouts, subscriptions, alerts, and official collections, models, metrics, and questions. Apache Superset documents a no-code visualization builder and a SQL IDE. Its site says SQL Lab supports custom SQL queries, database metadata browsing, and Jinja templating. For visualization, Superset lists 40+ pre-installed visualization types, including support for detailed geospatial charts, alongside custom visualizations through its plug-in architecture. Our research does not support a general conclusion about which interface is easier for a particular team.
What deployment and governance details are publicly documented?
Metabase documents both self-hosting and Metabase Cloud, with Cloud handling setup, backups, and upgrades. It also states that Enterprise can provide an air-gapped deployment, a dedicated success engineer, procurement help, and a 1-day support SLA; air-gapped deployment has an additional fee. Its pricing page lists row- and column-level permissions, SSO, required 2FA, IP allowlists, caching controls, usage analytics and auditing, multi-tenant embedded analytics, and AI usage auditing and controls on Pro. Apache Superset’s website directs administrators to documentation covering installation, configuration, security, and database drivers. It also documents feature flags, data caching, dashboard filters, CSS templates, and datasets. Our research does not include equivalent Superset commercial support, deployment, or identity-provider pricing details.