How PostGIS helps power place intelligence

In the early days of location intelligence, teams often used a Franken-stack: one system for attributes, another for maps, and something else holding the weird bits together.

We still love weird bits. We just prefer not to make the customer pay for the chaos.

At Place Signals, we rely on PostGIS as the spatial engine underneath the rest of the stack.

Why it matters

PostGIS lets us keep geography close to the data instead of treating maps like a separate hobby.

That means we can do things like:

• query spatial relationships directly
• combine geography with other signals
• keep the scoring logic close to the source of truth

Why H3 is part of the picture

For large-scale aggregation, PostGIS works even better when we pair it with H3.

H3 gives us a consistent hexagonal grid that makes it easier to compare places without the usual geometry headaches.

That helps us:

• normalize messy boundaries
• speed up joins
• store precomputed scores at a stable resolution

Why this is useful

Most of the value is boring in the best possible way.

It means the product can answer questions faster, the geometry stays cleaner, and the scores are less likely to get weird because one boundary decided to be dramatic.

Bottom line

PostGIS is not just a database.

It is the part of the system that keeps the geography from turning into a mood board.

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Sources and data notes

• PostGIS 3.6 / PostgreSQL 18 technical benchmarks.
• H3 Hierarchical Geospatial Indexing, v4.1 Documentation.
• Place Signals Core Engineering, Spatial Scoring v3.2.