Do I need PostGIS, or is a geohash column enough?

A geohash string column plus a 9-cell query and a Haversine filter handles point-radius search to several million rows with no extension and no new service. Reach for PostGIS when you need shapes rather than points: polygon containment for delivery zones, line distance for routes, or genuine spherical accuracy at high latitudes.

How do I choose the geohash precision?

Pick the shortest length whose cell still exceeds your search radius, so the 3 by 3 block is guaranteed to cover the whole circle. For a 1 km radius that is 6 characters at 610 m. If your radius varies per query, store several prefix lengths as separate columns and pick at query time rather than recomputing.

Why does everyone still run a distance calculation at the end?

Cells are rectangles and a radius is a circle, so a cell query returns a superset that includes corners outside the radius. The index exists to make the candidate set small, not to be correct on its own. Haversine over a few hundred candidates costs microseconds and is what makes the answer exact.

Databaseschapter 5 of 5 · 4 lessons

Geospatial Indexing

Turn latitude and longitude into a sortable key so "what is near me" becomes a range scan.

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A user opens your app in London and asks for restaurants within 5 kilometres.

You write what looks obvious: select everything where latitude is between two numbers and longitude is between two numbers. You have indexed both columns. It returns in 8 milliseconds on your laptop against 3,000 rows.

In production, against 8 million rows, it takes 1.9 seconds. Your database used the latitude index, pulled back 40,000 rows in that band stretching right across Europe, and threw away 39,000 of them one at a time for having the wrong longitude.

Both columns are indexed and the query is still doing almost all its work by hand. Understanding why is the whole chapter, and the reason a separate family of indexes exists for this.

Lessons

4 in this chapter

Why Two Dimensions Break IndexesA B-tree sorts on one axis. Nearness needs both at once.2 min
GeohashInterleave the bits of both coordinates and closeness becomes a shared prefix.2 min
The Boundary ProblemTwo shops across the street from each other can share no prefix at all.2 min
Quadtrees and HexagonsFixed grids waste space on empty land and choke on dense cities.3 min