Physical AI news and engineering for real-world data

Spatial Data Processing Platforms: A Comparison of Enterprise and Cloud-Native Options

For Data Engineers and Architects Evaluating Spatial Workloads on Snowflake, Databricks, and PostGIS Six platforms dominate spatial data processing today: PostGIS  for transactional workloads under 100GB, Snowflake and BigQuery GIS for light spatial enrichment inside a broader analytics platform, Databricks  for vector spatial joins on the Lakehouse, Apache Sedona for self-managed open-source distributed spatial compute, […]

Spatial Data Pipeline Architecture: PostGIS and Wherobots Together

In the world of data architecture, there is a dangerous myth that you have to choose “one tool to rule them all.” We often see organizations paralyzed by the debate: “Should we use a Database or a Data Lake?” A spatial data pipeline architecture built for both large-scale analytics and operational queries is one of […]

Iceberg v3 Gets Native Geo Types. It’s More Than a Format Upgrade

Introduction Geospatial data touches nearly every industry, and until recently, the open lakehouse had no native way to handle it. Snowflake recently announced Iceberg v3 support with native geometry and geography types. It’s the first major engine to ship the geospatial extensions to the Iceberg spec. These types are now part of the open standard, […]

Mobility Data Processing at Scale: Why Traditional Spatial Systems Break Down

A Wherobots Solution Accelerator for GPS Mobility Analytics — Part 1 of 2

PostGIS vs Wherobots: What It Actually Costs You to Choose Wrong

When building a geospatial platform, technical decisions are never just technical, they are financial. Choosing the wrong architecture for your spatial data doesn’t just frustrate your data team; it directly impacts your bottom line through large cloud infrastructure bills and, perhaps more dangerously, delayed business insights. For decision-makers, the choice between a traditional spatial database […]