superset open source analysis

Apache Superset is a Data Visualization and Data Exploration Platform

Project overview

⭐ 68988 · TypeScript · Last activity on GitHub: 2025-11-15

GitHub: https://github.com/apache/superset

Why it matters for engineering teams

Apache Superset addresses the challenge of making complex data accessible and understandable for engineering teams by providing a robust platform for data visualisation and exploration. It is particularly suited for data engineers, data scientists, and business intelligence professionals who require a production ready solution to create interactive dashboards and perform in-depth analytics. Superset is mature and reliable, having been widely adopted in production environments across various industries, supported by an active open source community. However, it may not be the right choice for teams seeking a lightweight or fully managed service, as it requires self hosting and operational overhead. Additionally, projects with minimal data visualisation needs might find simpler tools more appropriate.

When to use this project

Superset is a strong choice when teams need a scalable, self hosted option for interactive data visualisation that integrates well with SQL-based data sources. Consider alternatives if you require a fully managed cloud service or if your use case demands minimal setup and simpler reporting features.

Team fit and typical use cases

Data engineers and BI teams benefit most from Superset as an open source tool for engineering teams to build and share complex dashboards and reports. Typically, it is used to visualise large datasets, monitor key business metrics, and support data-driven decision making in products ranging from internal analytics platforms to customer-facing business intelligence solutions.

Topics and ecosystem

analytics apache apache-superset asf bi business-analytics business-intelligence data-analysis data-analytics data-engineering data-science data-visualization data-viz flask python react sql-editor superset

Activity and freshness

Latest commit on GitHub: 2025-11-15. Activity data is based on repeated RepoPi snapshots of the GitHub repository. It gives a quick, factual view of how alive the project is.