4 ms·
It would depend on where most of the processing is happening. PostGIS gives you the benefit of spatial indexes which are extremely performant. I've seen Pytho
by gabegm 3y ago
It would depend on where most of the processing is happening.
PostGIS gives you the benefit of spatial indexes which are extremely performant.
I've seen Python GeoSpatial applications taking hours to finish processing which only took a few minutes when shifted onto PostGIS.
If you're also doing a lot of processing in Python, exploring other languages could also help. In the case of Julia you get a typed language that's also JIT compiled.
- qfwfq_ 3y agoGeopandas has had spatial indexing available for quite a long time... https://geopandas.org/en/stable/docs/reference/sindex.html https://geopandas.org/en/stable/docs/reference/sindex.html I think that the challenge for most is that the PostGIS query planner does the indexing for you in most queries, while a naive all-pairs comparison in geopandas/shapely won't tell you to use the .sindex attribute instead.