Planetary-scale answers, unlocked.
A Hands-On Guide for Working with Large-Scale Spatial Data. Learn more.
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Apache Sedona has reached ⭐ 2M+ downloads ⭐ in the past month!
Our newest features include KNN Join, GeoStats and DataFrame-based readers. Learn more about the latest release in our most recent office hour.
You can can access the presentation slides here and the kNN Join slides here. Be sure to save the date for the next office hour to stay up-to-date with the latest releases!
Spatial data should be treated as a first class citizen. Here’s an overview of Apache Sedona and some of its common use cases. Learn more.
A machine learning and statistical toolbox for WherobotsAI and Apache Sedona users. Learn about its use cases and what challenges it helps solve. Read more.
Ideal for developers, data scientists and engineers, this hands-on guide provides practical solutions for challenges in working with various types of geospatial data. Get access here.
Hear from an amazing lineup of speakers from the Google Maps and Google Earth teams, former ESRI and Wherobots. Topics include kNN Join, the origins of GIS Day, the history and future of cloud-native geospatial technology, and current work within the open source community. More details here.
Learn>Learn how WherobotsAI Raster Inference enables data platform and science teams to analyze our planet with satellite imagery faster, more reliably, and with a zero carbon footprint—using SQL and Python. This fully managed, high-performance, carbon-neutral planetary-scale computer vision solution makes AI/ML on satellite imagery accessible to most developers and data scientists.
We host monthly office hours as a way to engage with the community, share the latest updates and releases, along with future plans. If you’re working on something exciting with Apache Sedona, we’d love to hear about it. Save the date for the next office hour.
Key takeaways
Download stats, Sedona 1.7.0 (kNN Join, GeoStats, DataFrame readers), a What is Apache Sedona overview, GeoStats, an O’Reilly Sedona guide, Spatial Data Science Conference recap, and upcoming meetup, re:Invent, and office-hour dates.
It says Apache Sedona reached 2 million+ downloads in the past month.
Expo booth #1865 all week, a GeoParty on December 4 at the Venetian Pool Deck (registration required), and a Raster Inference session on December 5 from 12:30–12:50 PM at Venetian Hall B Expo, Theater 4.
kNN Join, GeoStats, and DataFrame-based readers, with office-hour slides linked from the newsletter.
RasterFlow is now available in Public Preview
RasterFlow makes planetary-scale earth intelligence workflows easy and costs predictable. We are excited to announce that RasterFlow is now in Public Preview, opening up the power of planetary scale Earth Intelligence to all Wherobots Professional Edition customers! RasterFlow let’s you solve complex monitoring challenges with vision-language models or tailored models for specific use cases, without […]
Wherobots for QGIS: Cloud-Scale Spatial Data, from Wherobots Labs
Wherobots for QGIS is a new plugin that connects QGIS to Wherobots Cloud. From a panel inside QGIS, an analyst can run spatial SQL against WherobotsDB, load the results as a map layer, push a local layer up to a Wherobots Iceberg table, and pull raster data into the canvas. Why Wherobots for QGIS: Eliminating […]
How Wherobots builds with NVIDIA to let AI see the physical world
The world and what happens in it is digitized by petabytes of raw and derivative spatial datasets of various data types and scales, and the potential for applying AI to it is immense. But the AI models and agents we use every day need connectivity to tools that turn this data into usable insights and relationships. Wherobots gives AI the ability operate on and understand raw physical-world data, and NVIDIA GPUs are core to it. Architecturally here’s how this works at a high level.
El Niño 2026, atmospheric rivers, and California’s burn scars: one SQL engine, two data models
7,713 mapped building footprints sit inside or within 500 m (1,640 ft) of the 42 Eaton basins USGS rates high hazard for debris flows, and 388 km (241 mi) of mapped road and path cross the low ground below the scar. WherobotsDB finds both in SQL: a join to the USGS basins for the buildings, and a raster vector join over elevation for the roads.
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