A database that is optimized for storage and querying of data related to objects in a space, which includes lines, points, and polygons, is called a spatial database. Various fields of study have multiple applications for managing geometric data, geographic data, and spatial data. In these databases, a “space” can be geographic like a map of the earth’s surface, geometric like a layout of a very large scale integration (VLSI) design, or spatial like a 3-D representation of protein molecule chains. The spatial database is similar to a standard database with additional abilities for spatial data handling. For example, spatial data types (SDTs) are offered in a spatial database’s query language and data model.
When a spatial database is used for geographic mapping, its SDTs indicate structure in a space, such as points, lines and regions, and relationships among structures, such as lines intersecting one another. A user may see these entities represented by roads, pipelines, or forests on a map, but in a programming view they are represented by lines, polygons or points. These types of databases are called object-based spatial databases. Additionally, topological relationships, such as overlapping or disjointing of lines, and directional relationships, such as the cardinal compass directions, are represented and programmed into a geographic spatial database. Metric relationships, which indicate the distance of objects, are also represented in these databases.
Spatial databases are used for business, government, marketing, and commercial data. A business may map concentrations of where a certain type of customer is located to plan the best place to construct another building, or a politician may survey a voting demographic to plan a campaign route. They can also be used for planning of cities and regions or used by police jurisdictions for crime pattern analysis. SDTs can be simple information, but they can also become very complex if what the user needs to know is very specific. These complex relationships of objects in the space are what make spatial databases beneficial because they can use and sort through massive amounts of information.
Oftentimes, specific objects in a certain spatial database have a number of variables associated with them. In this case, a spatial database can use structured query language (SQL) to provide special index functions for manipulating and querying data. While it could be used solely for storage, the database can be used for much more, including analysis of data. Objects in the database can contain an infinite amount of variables, and special spatial database tools allow for sorting of the various pieces of information.
