awesome-open-source-data-engineering

Why we included this project

Building an analytics platform usually means juggling a dozen different tools, and this list gives you a single map of the whole data engineering stack. The table of contents groups entries by function, from storage and data lake platforms through integration, processing, workflow management, metadata, and analytics, with an ML/AI platform section near the end. Grouping by function rather than popularity makes it practical for comparing alternatives within a layer, such as distributed SQL databases or workflow engines. The list also flags inactive projects, so you can avoid adopting something that is no longer maintained. For a team that wants a broad survey before committing to specific tooling, this is a useful starting point.