Metabase

Used for data visualization, dashboard creation, and business intelligence analytics.

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  • Overview
  • Features
  • Pricing
  • Pros
  • Cons
  • Reviews

Metabase Overview

  • Updated September 1, 2025

Metabase is an open-source business intelligence and analytics platform designed for data exploration and visualization. It enables users to create interactive dashboards, generate insightful reports, and perform ad-hoc queries without requiring advanced technical skills.

With a user-friendly interface, Metabase supports connections to various databases, allowing teams to analyze data, track key metrics, and share insights efficiently, making data-driven decision-making accessible to organizations of all sizes.

Key Features

Intuitive Query Builder: Users can create complex queries without SQL knowledge, and the point-and-click interface simplifies data exploration.
Interactive Dashboards: These allow customization with charts, graphs, and tables, which provide a comprehensive view of data tailored to business needs.
Data Visualization Options: Metabase offers various chart types like bar, line, pie, and scatter plots, and users can customize colors, labels, and scales for clarity.
SQL Editor: Advanced users can write custom SQL queries, which provide flexibility for complex data analysis and manipulation.
Data Source Integration: The platform connects to databases like MySQL, PostgreSQL, MongoDB, and cloud services such as Google BigQuery, and this ensures comprehensive data access.
Sharing and Collaboration: Users can share dashboards and reports via links, email, or integrations like Slack, and this fosters team collaboration.
Embedding Capabilities: Metabase allows integration of charts and dashboards into applications, and options include public or signed embedding for secure, customized displays.
Automated Alerts and Notifications: Users can set up alerts for specific data conditions, and these ensure timely notifications for critical metrics.
Collections: These organize questions, dashboards, and models like folders, and they help manage permissions and group related content.
Models: Curated datasets combine and filter data from multiple tables, and they provide a simplified starting point for queries.
Metrics: These standardize calculations for key numbers like revenue, and they ensure consistency across dashboards and reports.
Natural Language Querying (NLQ): Users can ask questions in plain English, and the platform generates relevant visualizations, which simplifies data access.
Data Drill-Through: This feature allows exploration of specific data points within charts, and it facilitates deeper insights.
Usage Analytics: Metabase provides insights into how dashboards and data are used, and this helps teams identify engagement and improvement areas.
Row-Level Security and Permissions: Administrators can restrict data access based on user roles, and this ensures data security and compliance.
Mobile Accessibility: The responsive design allows access from mobile devices, and this ensures data insights are available on the go.
Data Sandboxing: This restricts data access at the row level based on user attributes, and it personalizes data views for security.
CSV Upload: Users can analyze data from CSV files directly, and this supports teams without existing databases.
API and Data Export: The API enables programmatic interaction, and export options like CSV, Excel, or PNG support broader data sharing.
Time-Series Analysis: This supports visualization of temporal patterns, and it aids trend analysis and forecasting.

Price

  • Open Source: Free, self-hosted, core BI features, unlimited charts/dashboards, static embedding with watermark, community support. Best for freelancers.
  • Starter: $85/month (5 users included, $5/additional user), cloud-hosted, core BI features, static embedding with watermark, 3-day email support. Best for small teams.
  • Pro: $500/month (10 users included, $10/additional user), cloud or self-hosted, SSO, granular permissions, interactive embedding, white-labeling, usage analytics. Best for middle-sized teams.
  • Enterprise: Custom pricing (starts at $15k/year), all Pro features, priority support, dedicated success engineer, optional professional services. Best for large teams.

Check pricing details: https://www.metabase.com/pricing

Pros

Competitor

Pros of Metabase
Looker Metabase offers a free, open-source plan that provides robust data visualization and query-building capabilities, and this makes it more accessible for freelancers and small teams with limited budgets. Its intuitive interface requires no prior SQL knowledge, which simplifies adoption for non-technical users.

Looker, priced at approximately $3,000-$5,000/month for 10 users, demands a data team and technical expertise for its LookML modeling, whereas Metabase’s simplicity and lower cost suit smaller organizations. Customer reviews praise Metabase’s ease of setup and user-friendly dashboards, which deliver quick insights without the complexity of Looker’s enterprise-focused features.
Tableau Metabase’s open-source version is free, and this provides a cost-effective alternative to Tableau’s $15/user/month pricing. Its visual query builder allows non-technical users to create reports easily, which contrasts with Tableau’s steeper learning curve for advanced analytics.

Metabase supports a wide range of databases like MySQL and PostgreSQL, and its lightweight setup is ideal for smaller teams. Reviews highlight Metabase’s straightforward dashboard creation and live data reporting, which offer flexibility for businesses without Tableau’s resource-heavy infrastructure.
Microsoft Power BI Metabase’s free open-source plan contrasts with Power BI’s $13.70/user/month Pro plan, and this makes it a budget-friendly choice for startups. Its platform-agnostic design connects to diverse databases, unlike Power BI’s tight integration with Microsoft ecosystems.

Metabase’s point-and-click interface is highly intuitive, and customer reviews commend its ease of use for non-technical users. It also avoids Power BI’s reported sluggishness with complex datasets, and this ensures smoother performance for basic reporting needs.
Amazon QuickSight Metabase’s open-source plan is free, unlike QuickSight’s subscription-based model, and this appeals to cost-conscious users. Its user-friendly query builder and dashboard creation require minimal technical skills, which contrasts with QuickSight’s focus on AWS integration.

Reviews note Metabase’s quick setup and ability to handle live data effectively, and its self-hosted option enhances data security compared to QuickSight’s cloud-only approach. Metabase’s community support adds value for smaller teams.
Domo Metabase’s free, self-hosted option undercuts Domo’s higher pricing, which is not publicly listed but noted as expensive. Its simplicity in creating visualizations and dashboards suits non-technical users, and this contrasts with Domo’s complex feature set requiring more training.

Metabase’s compatibility with various databases ensures flexibility, and reviews praise its cost-effectiveness and ease of use. It also avoids Domo’s reported slow performance during team collaboration.
Apache Superset Both Metabase and Superset are open-source, but Metabase’s interface is more intuitive for non-technical users, and this reduces the learning curve compared to Superset’s developer-focused design. Metabase’s query builder simplifies data exploration, and its dashboard creation is streamlined.

Customer reviews highlight Metabase’s ease of setup and user-friendly visualizations, which make it more accessible than Superset’s technical setup for teams without data engineers.
Holistics Metabase’s free open-source plan contrasts with Holistics’ $100/month starting price, and this makes it ideal for budget-conscious teams. Its visual query builder is more accessible for non-technical users than Holistics’ data modeling focus. Reviews praise

Metabase’s quick setup and live data reporting, which provide immediate value. Its self-hosted option also offers greater control compared to Holistics’ cloud-based approach, appealing to security-conscious organizations.

Cons

Competitor

Cons of Metabase
Looker Metabase lacks Looker’s advanced semantic modeling and LookML, and this limits its ability to handle complex data workflows for large enterprises. Its embedding capabilities are basic, with static iframes and watermarks, whereas Looker offers secure, white-labeled embedding.

Customer reviews note Metabase’s slower performance with large datasets, and its open-source version lacks Looker’s robust support and governance features, which are critical for enterprise-scale deployments.
Tableau Metabase’s visualization options are less advanced than Tableau’s, and this restricts customization for complex dashboards. It lacks Tableau’s deep drill-down and interactive filtering capabilities, which are preferred by data analysts.

Reviews highlight Metabase’s stability issues, such as occasional graph crashes, and its limited data governance compared to Tableau’s robust security and compliance features, which make it less suitable for large organizations with complex needs.
Microsoft Power BI Metabase does not match Power BI’s extensive library of over 500 connectors, and this limits its integration with diverse data sources. Its visualization capabilities are less robust, and reviews note slower load times with complex datasets compared to Power BI’s performance.

Metabase’s open-source version lacks Power BI’s advanced security features like end-to-end encryption, and its customer support is limited to community forums, unlike Power BI’s comprehensive resources.
Amazon QuickSight Metabase’s data source integrations are fewer than QuickSight’s, and this restricts its use for organizations with diverse cloud-based systems. Its visualization options are less sophisticated, and reviews mention occasional performance lags, unlike QuickSight’s optimized cloud performance.

Metabase’s open-source support is limited to forums, whereas QuickSight offers AWS-backed support, and this makes it less reliable for mission-critical applications requiring rapid assistance.
Domo Metabase lacks Domo’s extensive 1,000+ connectors and AI-powered insights, and this limits its appeal for organizations needing broad integrations. Its visualization options are less varied than Domo’s 150+ chart types, and reviews note performance issues during team collaboration.

Metabase’s governance features are minimal compared to Domo’s GDPR and HIPAA compliance, and its open-source plan lacks the dedicated support Domo provides for enterprise users.
Apache Superset Metabase’s customization options for visualizations are less extensive than Superset’s, and this can limit flexibility for technical teams. Its performance can be slower with large datasets, as noted in reviews, whereas Superset handles SQL-based dashboards efficiently.

Metabase lacks Superset’s advanced RBAC and OAuth support, and its open-source version relies on community forums, which may not match Superset’s developer-focused community for technical troubleshooting.
Holistics Metabase does not offer Holistics’ semantic modeling or dbt integration, and this restricts its use for teams needing reusable metrics. Its embedding capabilities are less advanced, with limited control compared to Holistics’ secure options.

Reviews note Metabase’s slower query performance and lack of version control, and its governance features are weaker than Holistics’ support for cross-database joins and ELT capacities, which are critical for data-driven organizations.

Customers' Reviews From Reliable Websites

Reddit Review
G2 Review
Gartner Review
Capterra Review
Glassdoor Review