Why Apache Sedona Might Replace Half Your Geospatial Stack

Most GIS tools crash when your data gets big. Millions of points, thousands of polygons, terabytes of rasters — and suddenly your workflow grinds to a halt. That’s where Apache Sedona comes in. Built on Apache Spark, Sedona lets you process massive geospatial datasets at scale — whether you’re working with vector or raster data, GeoParquet or cloud-optimized GeoTIFFs. In this video, we’ll break down: 🔹 What Apache Sedona actually is (and how it compares to PostGIS and GeoPandas) 🔹 When you should and shouldn’t use it 🔹 How Sedona handles raster + vector data in the cloud 🔹 Why SedonaDB makes it easier than ever to start with no cluster setup 🔹 And how to integrate it with tools like Databricks, AWS, and Wherobots If you’ve ever wondered how to scale your GIS workflows without breaking your computer this video will show you how. 🔗 Resources mentioned: Apache Sedona: https://sedona.apache.org SedonaDB Docs: https://sedona.apache.org/sedonadb/la... Wherobots Cloud: https://wherobots.com --- 📊 FREE: The Modern GIS Skill Map The 5 skills that actually matter in modern GIS (and what you can stop learning). Based on a survey of 1,400+ geospatial professionals. ➡ Get the free training + PDF guide: https://forrest.nyc/go/training/ 0:00 Simplify Your Spatial Stack with Sedona 0:40 What is Apache Sedona 4:10 Why should you care about Apache Sedona 7:45 Do you need to use Apache Sedona 11:27 How to use Apache Sedona 14:39 Pitfalls with Apache Sedona 16:29 When not to use Apache Sedona 17:55 Where to learn more about Apache Sedona CONNECT WITH ME 📸 Instagram:   / matt_forrest   💼 LinkedIn:   / mbforr   📧 Newsletter: https://forrest.nyc 🌐 Website: https://forrest.nyc