PostGIS for location intelligence in practice

PostgreSQL with the PostGIS extension is a powerful base for location intelligence: you get SQL, spatial indexing, and a rich set of functions without running a separate GIS stack. Here’s how we use it in production for site selection and catchment analysis.

Use case: site selection

For projects like fuel-station placement, we need to combine multiple layers: demographics, traffic flow, existing network, and terrain. PostGIS lets us store and query all of this in one place. We use ST_Within, ST_DWithin, and ST_Intersects to define catchments and aggregate metrics per candidate site.

Performance tips

• Spatial indexes. Create GIST indexes on geometry columns and keep them updated.
• Simplify where possible. For analytics, simplified geometries often suffice and speed up queries.
• Pre-aggregate. For dashboards, we materialize aggregated results (e.g., by grid or region) instead of recomputing on every request.

Stack

Our services run in Docker, with PostGIS as the primary spatial store. We use Python for ETL and API layers, and occasionally QGIS or simple scripts for one-off analysis and validation.