For true geospatial data models that correctly implement most geospatial predicates and operators your only practical option is PostGIS or Oracle Spatial. This

For true geospatial data models that correctly implement most geospatial predicates and operators your only practical option is PostGIS or Oracle Spatial. This is a very complex and nuanced piece of mathematics and software engineering work that requires writing a massive amount of code, even most closed source databases don't do a real implementation due to the difficulty. Most developers are unaware of just how broken most half-assed implementations are; the databases do just enough to check a box but not actually be useful if you are doing real geospatial work. Geohashing has a lot of weaknesses and limitations, not really recommended unless your use case is very simple and not primarily geospatial in nature. The modern version was created in the 1990s and implemented by big database companies like Oracle and IBM (based on work in the 1960s and '70s). They deprecated that indexing feature in their database engines a long time ago for good technical reasons that apply to current open source implementations. Geospatial index performance is very sensitive to temporal and geometry distribution, and the performance variance can be extremely high. For non-trivial applications, the real world will eventually produce data that inadvertently executes a denial of service attack on naive geospatial databases.