Compute and AI for spatial data

The spatial intelligence cloud
from the original
creators
of Apache Sedona.

Companies Accelerating Outcomes with Wherobots and Apache Sedona

Use cases

Planetary Scale
analytics

Spatial joins

Perform spatial joins on millions of records for less than 50¢

GPS Map Matching at Scale

Match GPS points to roads for millions of records with no APIs

Detect Airplanes from Satellite Imagery with AI

Use text prompts and AI to find airplanes in satellie imagery for $2.50

Wherobots is lakehouse ready for AWS and Databricks Unity Catalog

Apache Sedona
Apache Parquet
Apache Iceberg
PyTorch

Benefits
for Data Practitioners

Up to 20x better performance, unlimited scale, at 1/n the cost

Wherobots runs faster at a lower cost with higher scale than other engines for processing physical world data.

Join Vector, Raster & Structured Data Seamlessly

Build a complete picture over space and time from every aspect.

AI for Satellite & Drone Imagery

Extract insights from imagery using pretrained or custom models.

SQL, Python, and Scala Ready

Build with the tools your team already knows.

Lakehouse ready with Apache Iceberg Included

Upserts, inserts, and transforms on spatial data at any scale.

Fully Compatible with Apache Sedona

Lower the cost of your existing workflows with zero code changes.

How it works

Turn spatial data into products
you can build on
in your Lakehouse

For teams focused on

“Overture’s 2.6B-building dataset now runs up to 20x faster on Wherobots, with a simple code redirect that kept Sedona compatibility and made our team more productive.”

Jennings Anderson
Software Engineer with Meta for Overture

“With Wherobots on AWS, we can now scale to millions of acres reliably and cost-effectively—delivering faster results and more value to our customers.”

G. Bailey Stockdale
CEO Leaf Agriculture

“With Apache Sedona, we process millions of fleet-derived traffic signs, using scalable spatial joins and partitioning to automate map updates—enhancing Amazon Last Mile’s delivery networks for faster, more reliable routing.”

Arka Pratim Das
Sr. Manager, Software Development, Amazon Maps

“Getting data, algorithms, and compute in one place with Spark/Sedona notebooks is a huge boost—powerful like Earth Engine, but with the control developers need to get jobs done.”

John Powell
Sr. Geospatial Data Engineer, AddressCloud

39 days of processing reduced to <1 day—delivering faster, more accurate population insights to our logistics and supply chain customers worldwide.”

Jerome Urbain
Head of Products at GeoPostcodes
Sphere

Get started

Modernize your spatial data
in the lakehouse today.