GeoDa is a free and open source software tool that serves as an introduction to spatial data analysis. It is designed to facilitate new insights from data analysis by exploring and modeling spatial patterns.

GeoDa was developed by Dr. Luc Anselin and his team. The program provides a user-friendly and graphical interface to methods of exploratory spatial data analysis (ESDA), such as spatial autocorrelation statistics for aggregate data (several thousand records), and basic spatial regression analysis for point and polygon data (tens of thousands of records). To work with big data in GeoDa it should first be aggregated to areal units. Since its initial release in February 2003, GeoDa's user numbers have increased exponentially to over 300,000 (August 2019). This includes lab users at universities such as Harvard, MIT, and Cornell. The user community and press embraced the program enthusiastically, calling it a "hugely important analytic tool," a "very fine piece of software," and an "exciting development."

Pygeoda is a python library that wraps all core functions of spatial data analysis in GeoDa and libgeoda. Unlike the desktop software GeoDa, libgeoda is a non-UI and feature focused C++ library that is designed for programmers to do spatial data analysis using their favoriate programming languages (R, Python, Java etc.). It also aims to be easily integratd with other libraries, softwares or systems on different platforms.

There is also Rgeoda. Rgeoda is a R package that wraps all core functions of spatial data analysis in GeoDa and libgeoda. Unlike the desktop software GeoDa, libgeoda is a non-UI and feature focused C++ library that is designed for programmers to do spatial data analysis using their favoriate programming languages (R, Python, Java etc.). It also aims to be easily integratd with other libraries, softwares or systems on different platforms.