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Spatial database management systems
von Matthias Gelbmann, 6. April 2021
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What is a Spatial DBMS
A Spatial DBMS is a database management system that is able to efficiently store, manipulate and query spatial data. Spatial data represent objects in a geometric space, for example points and polygons.
While any DBMS can store simple spatial data, e.g. in form of (x,y) coordinates, we expect more from a Spatial DBMS. Spatial DBMSs typically provide dedicated data types to store also more complex types of spatial data. Additionally, they implement spatial indices to optimize the access to sets of spatial data. Spatial indices allow, for example, to efficiently retrieve points that are within a certain distance of other objects. Furthermore, spatial DBMSs provide features to perform operations on objects or to manipulate objects. Examples are computing distances between complex spatial objects, merging or intersecting objects, and calculating properties of objects, such as areas of polygons.
Specialized Spatial DBMSs
Geospatial data are an important subset of spatial data, dealing with data that describe locations on the Earth's surface. Geographic information systems (GIS) are able to work with geospatial data.
Spatio-temporal data are another common variation, where spatial data is combined with time stamps, and thus offering another dimension for data storage and manipulation.
Spatial DBMS Ranking
The most popular Spatial DBMS at the moment are
- PostGIS, a spatial extension of PostgreSQL.
- SpatiaLite, a spatial extension of SQLite.
- GeoMesa, a spatio-temporal DBMS which can use various systems as storage layer.
You can see all systems in the Spatial DBMS ranking.
There are also a fair number of DBMSs that support the spatial model as secondary database model, including 8 of the top 10 systems in our ranking. See our explanation about how and why we distinguish between primary and secondary database models.
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