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If you're looking to build the ideal modern data stack for analytics using only open-source tools, we cover the top alternatives to your favorite paid solutions.
Note: While some technologies listed in this guide are not open-source but source-available per their licenses, we believe it's important to list and evaluate them alongside since the license, in most cases, wouldn't have a material effect on how a typical data team would leverage the technology.
Putting together an effective, scalable, cost-efficient data stack is challenging. The industry has made enormous strides over the past 10 years, and many technologies and products exist.
As data practitioners who also grapple with the same challenges, we aim to provide an overview of the top technology choices for each part of a modern data stack. While we do our best to base our judgment on certain objective criteria looking into the development and release velocity of projects and diving deep into documentation, it is inevitably a subjective opinion like any technology recommendation is. Opinions are our own based on decades of combined experience as data leaders at multiple companies including Autodesk & Lyft.