BigQuery GIS
Spatial SQL at warehouse scale — powerful for analytics layers that don't need an enterprise geodatabase.
Why Google Cloud
Analytics-native cloud
GCP shines when geospatial joins warehouse-scale SQL. BigQuery geography types and Cloud Run services are a different shape than DynamoDB counters or ArcGIS Server farms.
Maps Platform adjacency
Google Maps and GCP billing/projects often travel together. Knowing both sides helps when products span map UX and cloud data.
Cloud Run simplicity
Containerized geospatial APIs without managing clusters — a clean contrast to Lambda and App Service.
Working across clouds
The point of this lab is not picking one cloud. It is knowing when BigQuery beats Athena, or when Maps Platform beats MapLibre.
Built on GCP
Playground projects
BigQuery and Cloud Run demos will land here as I expand beyond AWS-first labs.
BigQuery GIS
Spatial SQL notebook
Annotated BigQuery geography queries — buffers, joins, and tiling exports for web maps.
Coming soonCloud Run
Geo API on Cloud Run
A tiny geospatial API container — health checks, GeoJSON responses, and IAM notes.
Coming soonPlatform labs
Same pattern, more stacks
Mapping and cloud playgrounds — each hub explains why I use the platform and links demos as they ship.