PostGIS vs Traditional Databases
When to use a dedicated spatial database. An engineering deep-dive into spatial indexes, geometry types, and the performance benefits of PostGIS for location-heavy applications.
Most applications store location as two float columns — latitude and longitude — and get surprisingly far. You can display markers, filter by bounding box, even do a crude distance sort with the haversine formula. Then the requirements grow: polygons, containment, buffers, nearest-neighbor at scale. This is the moment teams discover why spatial databases exist.
What Geometry Types Actually Buy You
PostGIS makes geometry a native column type with hundreds of functions operating on it: ST_Contains, ST_Intersects, ST_Buffer, ST_Distance, and their many siblings. The point isn't the function count — it's correctness. Spatial predicates handle edge cases (shared boundaries, self-intersections, datum differences) that hand-rolled coordinate math gets subtly wrong, and subtle wrongness in spatial logic tends to surface as expensive business mistakes.
Equally important are the two distance worlds: geometry (fast, planar) and geography (slower, earth-accurate). Knowing when each is appropriate is half of practical PostGIS competence.
The Index Is the Product
The real magic is the GiST spatial index. A naive point-in-polygon check against a million parcels scans a million rows; with a spatial index, the candidate set collapses to a handful via bounding-box comparison before exact geometry is tested. Queries that would take minutes run in milliseconds. K-nearest-neighbor ordering (the <-> operator) gets the same treatment — 'closest 10 stores' stops being a full-table sort.
This is the difference in kind, not degree, from a traditional database: without spatial indexing, spatial queries simply do not scale.
When You Don't Need It
Honesty matters: if your spatial needs are 'store coordinates, show pins, maybe radius-filter a few thousand rows,' plain Postgres columns are fine, and simplicity wins. Reach for PostGIS when you have polygons, when containment and overlap questions appear, when row counts pass six digits, or when distance correctness starts affecting money.
Since PostGIS is an extension of the database you likely already run, the migration cost is low — which is exactly why it has become the default answer for serious location workloads.
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