Apache Superset

superset.apache.org ↗

Explore SQL-connected data with charts, dashboards and a SQL workspace.

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80/100
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Answers use saved listing facts and recorded sources.
Homepage screenshot
Screenshot of the Apache Superset homepage

What it does

Apache Superset is a data exploration and visualization application with a no-code chart builder, SQL editor and dashboards. It connects to supported SQL-speaking data systems rather than requiring a separate ingestion layer.

Apache Superset explores data in supported SQL databases through charts, dashboards and SQL Lab. It does not replace the source database with a separate storage service. Its Apache 2.0 licence permits free self-hosting, with the operator responsible for deployment and compatible database drivers.

Once a database and dataset are configured, open Datasets and select the dataset to enter Explore. The data and customization controls let you choose a chart, time column and metric. Click Run after changing the options to see the result, then Save the chart to a new or existing dashboard. Save and goto Dashboard opens the assembled result; Edit Dashboard lets you resize and arrange it.

A new dashboard can remain a draft. Use the Draft control beside its title to publish it for users whose permissions allow access. Publication does not remove the underlying data-access requirements.

The local Docker Compose quickstart includes an administrator login, but the project explicitly describes that setup as unsuitable for production. Use the production deployment guidance for a shared service. Reusable datasets and metrics can reduce repeated setup across charts, while SQL Lab gives analysts a query workspace for preparing data that needs more than visual selection.

Strengths

  • Offers visual chart building and a SQL workspace over connected data.
  • Datasets and metrics can be reused across charts.

Watch out for

  • A data source needs the required driver and dialect, and the deployment must be operated.

Best for

  • Technical data teams building internal dashboards over SQL data systems

Sources