Cloud Native Geospatial Analytics with Apache Sedona

Chapter 1. Introduction to Apache Sedona

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The open-source Apache Sedona project grew out of the need for a scalable geospatial analytics framework capable of working with large-scale spatial data. There’s a common saying in the data world that “spatial is special”. In other words, working with spatial data implies that due to the unique characteristics and complexities of spatial data, specialized techniques, tooling, and knowledge is required for effective analysis and interpretation of spatial data. While there is some validity to this perspective, it misses the more nuanced truth that many traditional best practices, techniques, tooling, and data formats from the data engineering and data science world are still perfectly relevant when working with geospatial data. However, there are some unique challenges and considerations that arise when working with spatial data.

In this chapter we will discuss some of the challenges that commonly arise when working with geospatial data and explore an ...