Apache Superset
Apache Superset: Open-source data exploration and visualization platform for all skill levels
About Apache Superset
Apache Superset is a modern, open-source platform designed for intuitive data exploration and visualization. It offers a no-code interface for quick insights, a powerful SQL IDE for advanced users, and seamless integration with modern databases. With 40+ pre-installed visualizations, scalable architecture, and self-serve analytics features, Superset empowers teams to build interactive dashboards, create custom datasets, and uncover data-driven insights efficiently.
FAQ
Superset can work with very large datasets. The performance depends on your underlying database's ability to execute queries and return results quickly. Superset acts as a thin layer for visualization, so the key is ensuring your data warehouse is optimized for speed.
The specifications depend on user activity, not dataset size. For a moderately-sized instance, 8GB RAM and 2vCPUs are adequate. Resource usage may spike during high activity, so monitor and adjust as needed.
Not directly in the Explore or Visualization UI. A Superset SQLAlchemy datasource is limited to a single table or view. For joins, use a view or SQL Lab, where you can write custom SQL queries (if your database account has access).
Follow the instructions in the 'Creating Visualization Plugins' documentation to build custom visualizations.
Yes, you can upload and visualize CSV data. Enable and use the CSV upload feature by following the instructions provided in the documentation.
Queries may time out due to long-running processes or gateway/proxy server limits. For SQL Lab, the default timeout is 6 hours, but you can adjust it in the configuration. For dashboard timeouts, check gateway settings and adjust SUPERSET_WEBSERVER_TIMEOUT in superset_config.py.
Superset is tested with MySQL, PostgreSQL, and SQLite as backends. While other databases may work, they are not officially supported. Column-store databases are not recommended for this use case.
Yes, Superset uses Scarf by default to collect basic telemetry data upon installation or usage. This data helps prioritize updates and security fixes. Users can opt out of telemetry collection as documented in the provided links.
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