Both https://typesense.org/ and https://duckdb.org/ (with their spatial plugin) are excellent geo performance wise, the latter now seems really production ready, especially when the data doesn’t change that often. Both fully open source including clustered/sharded setups.
No affiliation at all, just really happy camper.
We will have some more blog posts in the future describing different parts of the system in more detail. We were worried too much density in a single post would make it hard to read.
A while ago I tried to create something that has duckdb + its spatial and SQLite extensions statically linked and compiled in. I realized I was a bit in over my head when my build failed because both of them required SQLite symbols but from different versions.
But given that duckdb handles "take this n GB parquet file/shard from a random location, load it into memory and be ready in < 1 sec" very well I'd argue it's quite easy to build something that scales horizontally.
We use it for both the importer pipeline that processes the 2B row / 200GB compressed GBIF.org parquet dataset and queries like https://www.meso.cloud/plants/pinophyta/cupressales/pinopsid... and the sheer amount of functions[1] beyond simple stuff like "how close is a/b to x/y" or is "n within area x" is just a joy to work with.
[1] https://duckdb.org/docs/stable/core_extensions/spatial/funct...
You can also attach DuckDB to Apache Flight which will make it work beyond local operation.