Cloud-Native Geospatial Analytics with Apache Sedona

A Hands-On Guide for Working with Large-Scale Spatial Data

Navigating the complexities of large-scale geospatial data can be daunting—especially in cloud-native and distributed computing environments. Apache Sedona is an innovative distributed geospatial analytics engine built on Apache Spark, designed specifically to process, query, and analyze spatial data at scale. It is widely used across industries such as mobility, telematics, real estate, agriculture, climate science, financial services, and more.

Cloud-Native Geospatial Analytics with Apache Sedona provides real-world solutions to the challenges of working with massive geospatial datasets. This hands-on guide shows how to use Apache Sedona and Spatial SQL to build scalable spatial analytics pipelines in both local and cloud environments.

What You'll Learn

This guide will help you:

• Learn how to install and run Apache Sedona, both locally and in cloud environments
• Efficiently load, query, and analyze geospatial datasets using Spatial SQL as part of large-scale data pipelines and Spatial ETL processes
• Employ ML techniques to derive strategy-defining insights from spatial data
• Manage and optimize large-scale geospatial data within a data lakehouse architecture 

Who This Book is For

Ideal for developers, data scientists, and data engineers, this O’Reilly book provides real-world examples of how to leverage Apache Sedona, Apache Spark, and modern cloud technologies to unlock the full potential of cloud-native geospatial analytics at planetary scale.