MADlib is an open-source library for scalable in-database analytics. It provides data-parallel implementations of mathematical, statistical and machine-learning methods for structured and unstructured data.

The MADlib mission: to foster widespread development of scalable analytic skills, by harnessing efforts from commercial practice, academic research, and open-source development.


November 25th 2013: MADlib v1.4 is out!
New features include an improved interface for Multinomial logistic regression, Robust variance and clustered variance estimators for Cox Proportional Hazards, and NULL handling for various regression methods.

Binary packages are available for CentOS/RedHat and for Mac OS X. On other platforms, MADlib can be built from source. Our Wiki provides detailed instructions for deploying MADlib on PostgreSQL and Greenplum installations. For a list of new features, bug fixes, and known issues, please refer to the Release Notes.
As always, the MADlib forum is open for questions and discussions. Try it out and let us know about your feedback!

October 8th 2013: MADlib v1.3 is out!

September 10th 2013: MADlib v1.2 is out!

August 9th 2013: MADlib v1.1 is out!

July 5th 2013: MADlib v1.0 is out!


MADlib grew out of discussions between database-engine developers, data scientists, IT architects and academics, who were interested in new approaches to scalable, sophisticated in-database analytics. These discussions were written up in a paper in VLDB 2009 that coined the term "MAD Skills" for data analysis. The MADlib software project began the following year as a collaboration between researchers at UC Berkeley and engineers and data scientists at EMC/Greenplum.


Binary packages of the latest MADlib release:
• Mac OS X 10.6 and higher: Greenplum 4.1, 4.2 / PostgreSQL 9.0, 9.1, 9.2 (64-bit)
• CentOS / Red Hat 5 and higher (64-bit): Greenplum 4.1, 4.2 / PostgreSQL 9.0, 9.1, 9.2

Source Code:
• Snapshot of development repository: .zip .tar.gz
• Latest stable release (v1.4.1): .zip .tar.gz


Installation guides can be found in the MADlib Wiki.

Documentation for the latest release:
• Users:
• Developers:

Pre-release documentation generated out of development repository:
• Users:
• Developers:

Additional Resources

MADlib Wiki
Project Roadmap
Contribution Guide
• User mailing list: List Information and Subscriptions, Browse Recent Posts
• Developer mailing list: List Information and Subscriptions, Browse Recent Posts
Bug reporting and feature requests: