A spatiotemporal database is a database that manages both space and time information. Common examples include:
Spatiotemporal databases are an extension of spatial databases and temporal databases. A spatiotemporal database embodies spatial, temporal, and spatiotemporal database concepts, and captures spatial and temporal aspects of data and deals with:
Although there exist numerous relational databases with spatial extensions, spatiotemporal databases are not based on the relational model for practical reasons, chiefly among them that the data is multi-dimensional, capturing complex structures and behaviours.
As of 2008, there are no RDBMS products with spatiotemporal extensions. There are some products such as the open-source TerraLib which use a middleware approach storing their data in a relational database. Unlike in the pure spatial domain, there are however no official or de facto standards for spatio-temporal data models and their querying. In general, the theory of this area is also less well-developed.[2] Another approach is the constraint database system such as MLPQ (Management of Linear Programming Queries).[3] [4]
GeoMesa is an open-source distributed spatiotemporal index built on top of Bigtable-style databases using an implementation of the Z-order_curve to create a multi-dimensional index combining space and time.
SpaceTime is a commercial spatiotemporal database built on top of the proprietary multidimensional index similar to the kd-tree family, but created using the bottom-up approach and adapted to particular space-time distribution of data.[5] In a study conducted by Ericsson, SpaceTime significantly outperformed GeoMesa.[6]