Redash
Redash is an open-source tool for writing SQL queries, visualizing results, and sharing dashboards. It is simpler than Metabase or Superset, with a focus on SQL-first workflows. It works well for small technical teams that need basic dashboards, but it lacks advanced features like semantic layers or drag-and-drop query builders. The project is less actively maintained since Databricks acquired it in 2020.
Official site ↗Why it ranks here
- Open-source and free; no licensing costs for self-hosting.
- SQL-first workflow is fast for technical users; no drag-and-drop abstraction.
- Simple setup: Docker container, connect your database, and start querying.
Where it sits
- Simpler than Metabase or Superset; fewer features but also less complexity.
- Behind Mode in SQL-first BI; Mode has better collaboration features and a stronger commercial backing.
- Not a replacement for enterprise BI; use it for small teams or internal ops dashboards.
How GTM Operations teams use it
- Small RevOps teams write SQL queries for pipeline and revenue metrics, then share static dashboards with sales leadership.
- Engineering teams use Redash for operational dashboards (app usage, error rates, API latency).
- Data analysts prototype dashboards in Redash before rebuilding them in Tableau or Looker.
- Internal ops teams at startups use Redash to track metrics on Postgres or MySQL without paying for BI tools.
In-depth notes
- Pricing: open-source and free for self-hosting. There is no official managed cloud offering after Databricks acquired the project.
- Less actively maintained since 2020; Databricks folded Redash into its platform, and the open-source community is quieter.
- No semantic layer: metrics live in individual queries. If you want consistency, enforce it through dbt or shared SQL snippets.
- Visualization options are basic: bar, line, pie, table. For custom or advanced charts, use Superset or Tableau.
- Good for side projects or small teams. If you need a more polished open-source tool, use Metabase or Preset.
Best for
Small technical teams that need simple SQL dashboards, or orgs that want free open-source BI for internal ops.
Avoid if
You need active maintenance and a growing ecosystem (use Metabase or Preset), or you want self-service for non-technical users (use Tableau or Sigma).
The rest of BI & analytics
Tableau Leader Visual analytics platform with drag-and-drop interface; Salesforce-owned market leader for interactive dashboards. #2 
Looker Leader Semantic layer (LookML) on live warehouse data; Google Cloud-owned platform for governed analytics with code-based modeling. #3 
Power BI Leader Microsoft's BI platform with deep Office and Teams integration; cost-effective for Microsoft shops with enterprise agreements. #4 
Omni Strong Modern warehouse-native BI with spreadsheet, SQL, and semantic model workflows; live queries with no extracts or cubes. #5 
Sigma Strong Warehouse-native BI with a spreadsheet interface; live queries on Snowflake, BigQuery, or Databricks with familiar Excel-like UX. #6 
Mode Strong SQL-first analytics platform with notebooks for analysis and reporting; popular with technical RevOps and data teams. #7 
ThoughtSpot Strong Search-driven analytics with natural language queries; AI-powered insights for business users who do not want to build dashboards. #8 
Hex Situational Notebooks for Python and SQL hybrid analysis; build interactive apps from notebooks with code and no-code cells. #9 
Domo Situational All-in-one platform with ETL, cloud data warehouse, and BI; higher total cost but unified vendor for orgs without a data stack. #10 
Qlik Situational Associative analytics engine for exploring complex data relationships; in-memory architecture with a steeper learning curve. #11 
Metabase Situational Open-source BI with simple setup and no-code query builder; good for small teams that need dashboards without enterprise complexity. #12 
Lightdash Niche dbt-native BI tool; metrics and dimensions defined in dbt YAML, dashboards built on transformed warehouse tables. #13 
Preset Niche Managed Apache Superset; open-source BI with commercial support, hosting, and enterprise features. Learning guide
Setup
Deploy Redash via Docker, connect to your database, and start writing SQL queries. Visualize results with basic charts and add them to dashboards.
First thing to build
Write a SQL query to count opportunities by stage, add a bar chart visualization, and create a dashboard with the chart. Share the dashboard link with stakeholders.
What actually matters
- Use query parameters to let users filter dashboards without editing SQL
- Schedule queries to run and email results on a cadence
- Set user permissions on data sources to control access
- Use query snippets to share common SQL fragments like date filters
Watch out
Less actively maintained since Databricks acquired it, so expect slower bug fixes and fewer new features.