Apache Superset

Move between no-code charts and a web SQL editor in one BI workspace

Analysts can build charts through the GUI or query directly in the web-based SQL Editor. A lightweight semantic layer defines reusable custom dimensions and metrics for dashboards and exploration.

Sources: [2]

Connect to a wide range of SQL warehouses and databases through the SQLAlchemy/DB-API ecosystem

The README states that Superset can query SQL-speaking datastores and engines with Python DB-API drivers and SQLAlchemy dialects. Its documented ecosystem includes systems such as BigQuery, Snowflake, PostgreSQL, ClickHouse, Trino, and Athena, alongside caching, RBAC/authentication, APIs, and a cloud-native architecture.

Sources: [2]

For data teams combining SQL and GUI exploration across databases on infrastructure they control

It is a strong fit when organizations want BI integrated with their own authentication, data warehouses, and deployment environment rather than locking dashboards and metadata into one proprietary SaaS.

Docker Compose is explicitly not recommended for production; HA and operational services need a real production design

The official 6.1.0 Docker Compose guide says the single-host compose setup cannot meet high-availability requirements and is not supported or recommended for production. Treat it as a local evaluation/development path.

Production deployments need deliberate handling of database credentials, SECRET_KEY, authentication/RBAC, metadata storage, caching, asynchronous workers, backups, and upgrades. The 6.1.0 release also points operators to the project updating guide.

Sources: [4][3]