From the Spokane firestorm to all of Washington: real-time wildfire monitoring for under $50 a pass

The moment a satellite pass lands, this pipeline turns it into a burn-severity map in 14 minutes: real-time wildfire monitoring with Python and Spatial SQL that protects lives and assets, shown on the Spokane firestorm and scaled to the entire state of Washington.

How Bad Telemetry Data Sabotages Modern Fleets

By the Teams at Action Engine & Wherobots Fleet monitoring is undergoing a generational shift. Fleet monitoring, the systems that ingest and analyze vehicle telemetry to track fleet health, performance, and safety, has become the foundation of how operators run vehicles, not just track them. Modern vehicles generate orders of magnitude more telemetry than even […]

Spatial Data in Apache Iceberg: Optimizations and Management That Matter

Spatial data in Apache Iceberg needs different optimization than tabular data. A geometry column has no natural sort order, so unsorted files carry wide, overlapping bounding boxes and query planners cannot prune them… At all… This behaviour turns a selective spatial filter into a full table scan. A second problem compounds it: one oversized geometry […]

Streaming Spatial Data into Wherobots with Spark Structured Streaming

Real-time Spatial Pipelines Shouldn’t Be This Hard (But They Were) I’ve been doing geospatial work for over twenty years now. I’ve hand-rolled ETL pipelines, babysat cron jobs, and debugged more coordinate system mismatches than a person should reasonably endure in one lifetime. So when someone says “streaming spatial data,” my first reaction used to be […]

WherobotsDB is 3x faster with up to 45% better price performance

The next generation of WherobotsDB, the Apache Sedona and Spark 4 compatible engine, is now generally available.

Raster Processing at Scale: The Out-of-Database Architecture Behind WherobotsDB

Learn how WherobotsDB's out-of-database architecture processes terabyte-scale satellite imagery, elevation models, and sensor data at scale, enabling zonal statistics, raster algebra, and planetary-scale AI inference without custom infrastructure.

Scaling Spatial Analysis: How KNN Solves the Spatial Density Problem for Large-Scale Proximity Analysis

How we processed 44 million geometries across 5 US states by solving the spatial density problem that breaks traditional spatial proximity analysis