ingesting data into postgres makes sense for sparce data but not for dense data because it is waisting a lot of of space due to storage of coordinates with every data point and every weather variable. If you are using NOOA grib2 forecast files those are dense . Not to mention losing compression in postgres. TileDB will store data compressed, the dimension coordinates themselves will be compressed, plus column storage (each NetCDF variable) will make retrieval of dense weather data blazingly fast as oppose to postgres where you will have to scan the whole table
ingesting data into postgres makes sense for sparce data but not for dense data because it is waisting a lot of of space due to storage of coordinates with every data point and every weather variable. If you are using NOOA grib2 forecast files those are dense . Not to mention losing compression in postgres. TileDB will store data compressed, the dimension coordinates themselves will be compressed, plus column storage (each NetCDF variable) will make retrieval of dense weather data blazingly fast as oppose to postgres where you will have to scan the whole table