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Nº08 · Visualization

Apache Superset

Data exploration and BI dashboards, open-source and SQL-native.

PlatformIntroData Engineer·Data Scientist

What is it?

Apache Superset is an open-source business intelligence (BI) platform for exploring data and building interactive dashboards directly on top of SQL. It connects to dozens of databases and query engines without requiring you to move data into a proprietary store.

What is it used for?

  • Building visual dashboards with charts, tables, and interactive filters — no coding required.
  • Exploring data with SQL through its built-in web-based query editor (SQL Lab).
  • Connecting to many sources — PostgreSQL, MySQL, Trino, BigQuery, Redshift, DuckDB, and more — via SQLAlchemy as the connection layer.

When to use it / when not to?

Use it when your team needs shared dashboards on an existing SQL source, or when you want a self-service exploration tool without relying on a BI SaaS. It works especially well on top of engines like Trino or PostgreSQL where data is already organized.

Think twice if your team lacks the technical baseline to maintain it — Metabase is easier to get started with for small teams. If your use case is monitoring infrastructure or application metrics in real time, Grafana is a better fit. And if you only need static reports, a spreadsheet may be enough.

Get started in 1 minute

# With Docker Compose (fastest way to try it locally)
git clone https://github.com/apache/superset.git
cd superset
docker compose up

Superset starts at http://localhost:8088. Default credentials: admin / admin.

# Alternative: install with pip in an isolated environment
pip install apache-superset
superset db upgrade
superset fab create-admin
superset init
superset run -p 8088

Then add a database connection from Settings → Database Connections and start building charts on your own tables.

Quick trivia — test what you just read.

How much do you know about Apache Superset?

Official documentation

The source of truth lives there. Here we orient you; the depth is up to you.

Open official docs

What to learn next

See also

Nº08 · Updated 2026-06-08