Case Study: Apache Superset expands API access and data visualization with Preset

Apache Superset accesses APIs with Preset across 7 adapters

Apache Superset, an open-source business intelligence tool, faced the common user challenge of accessing and visualizing data stored in non-traditional sources like Google Sheets and various web APIs. This data was often locked away in spreadsheets or behind API endpoints, making it difficult to integrate directly into Superset's SQL-based environment for analysis and dashboard creation.

To solve this, Preset utilized Shillelagh, a Python library developed by a Superset contributor. This solution provided a SQL interface to numerous APIs, allowing Superset to natively query data from Google Sheets, AWS S3, GitHub, Socrata open data, weather services, and generic JSON endpoints. By implementing a Shillelagh database connection within Superset, Preset enabled users to seamlessly bring a vast array of external data directly into their BI workflows, significantly expanding the tool's connectivity and eliminating the need for complex data migration or manual exports.

Apache Superset