Most spatial databases allow the representation of simple geometric objects such as points, lines and polygons. Some spatial databases handle more complex structures such as 3D objects, topological coverages, linear networks, and triangulated irregular networks (TINs). While typical databases have developed to manage various numeric and character types of data, such databases require additional functionality to process spatial data types efficiently, and developers have often added geometryorfeature data types.
Geographic database (orgeodatabase) is a georeferenced spatial database, used for storing and manipulating geographic data (or geodata, i.e., data associated with a location on Earth),[a] especially in geographic information systems (GIS). Almost all current relational and object-relational database management systems now have spatial extensions, and some GIS software vendors have developed their own spatial extensions to database management systems.
The Open Geospatial Consortium (OGC) developed the Simple Features specification (first released in 1997)[1] and sets standards for adding spatial functionality to database systems.[2] The SQL/MM Spatial ISO/IEC standard is a part of the structured query language and multimedia standard extending the Simple Features.[3]
The core functionality added by a spatial extension to a database is one or more spatial datatypes, which allow for the storage of spatial data as attribute values in a table.[4] Most commonly, a single spatial value would be a geometric primitive (point, line, polygon, etc.) based on the vector data model. The datatypes in most spatial databases are based on the OGC Simple Features specification for representing geometric primitives. Some spatial databases also support the storage of raster data. Because all geographic locations must be specified according to a spatial reference system, spatial databases must also allow for the tracking and transformation of coordinate systems. In many systems, when a spatial column is defined in a table, it also includes a choice of coordinate system, chosen from a list of available systems that is stored in a lookup table.
The second major functionality extension in a spatial database is the addition of spatial capabilities to the query language (e.g., SQL); these give the spatial database the same query, analysis, and manipulation operations that are available in traditional GIS software. In most relational database management systems, this functionality is implemented as a set of new functions that can be used in SQL SELECT statements. Several types of operations are specified by the Open Geospatial Consortium standard:
Measurement: Computes line length, polygon area, the distance between geometries, etc.
Geoprocessing: Modify existing features to create new ones, for example by creating a buffer around them, intersecting features, etc.
Predicates: Allows true/false queries about spatial relationships between geometries. Examples include "do two polygons overlap?" or 'is there a residence located within a mile of the area we are planning to build the landfill?' (see DE-9IM)
Geometry Constructors: Creates new geometries, usually by specifying the vertices (points or nodes) which define the shape.
Observer Functions: Queries that return specific information about a feature, such as the location of the center of a circle.
Some databases support only simplified or modified sets of these operations, especially in cases of NoSQL systems like MongoDB and CouchDB.
Aspatial index is used by a spatial database to optimize spatial queries. Database systems use indices to quickly look up values by sorting data values in a linear (e.g. alphabetical) order; however, this way of indexing data is not optimal for spatial queries in two- or three-dimensional space. Instead, spatial databases use a spatial index designed specifically for multi-dimensional ordering.[5] Common spatial index methods include:
R-tree: Typically the preferred method for indexing spatial data.[6] Objects (shapes, lines and points) are grouped using the minimum bounding rectangle (MBR). Objects are added to an MBR within the index that will lead to the smallest increase in its size.
Aspatial query is a special type of database query supported by spatial databases, including geodatabases. The queries differ from non-spatial SQL queries in several important ways. Two of the most important are that they allow for the use of geometry data types such as points, lines and polygons and that these queries consider the spatial relationship between these geometries.
The function names for queries differ across geodatabases. The following are a few of the functions built into PostGIS, a free geodatabase which is a PostgreSQL extension (the term 'geometry' refers to a point, line, box or other two or three dimensional shape):[7]
Function prototype: functionName (parameter(s)) : return type
ArangoDB - a multi-model database which provides geoindexing capability.
Apache Drill - A MPP SQL query engine for querying large datasets. Drill supports spatial data types and functions [8] similar to PostgreSQL.
Esri Geodatabase (Enterprise, Mobile) - a proprietary spatial database structure and logical model that can be implemented on several relational databases, both commercial (Oracle, MS SQL Server, Db2) and open source (PostgreSQL, SQLite)
Caliper extends the Raima Data Manager with spatial datatypes, functions, and utilities.
CouchDB a document-based database system that can be spatially enabled by a plugin called Geocouch
Elasticsearch is a document-based database system that supports two types of geo data: geo_point fields which support lat/lon pairs, and geo_shape fields, which support points, lines, circles, polygons, multi-polygons, etc.[9]
H2 supports geometry types[10] and spatial indices[11] as of version 1.3.173 (2013-07-28). An extension called H2GIS available on Maven Central gives full OGC Simple Features support.
Any edition of IBM Db2 can be spatially-enabled to implement the OpenGIS spatial functionality with SQL spatial types and functions.
IBM Informix Geodetic and Spatial datablade extensions auto-install on use and expand Informix's datatypes to include multiple standard coordinate systems and support for RTree indexes. Geodetic and Spatial data can also be incorporated with Informix's Timeseries data support for tracking objects in motion over time.
Linter SQL Server supports spatial types and spatial functions according to the OpenGIS specifications.
MySQL DBMS implements the datatype geometry, plus some spatial functions implemented according to the OpenGIS specifications.[13] However, in MySQL version 5.5 and earlier, functions that test spatial relationships are limited to working with minimum bounding rectangles rather than the actual geometries. MySQL versions earlier than 5.0.16 only supported spatial data in MyISAM tables. As of MySQL 5.0.16, InnoDB, NDB, BDB, and ARCHIVE also support spatial features.
OpenLink Virtuoso has supported SQL/MM since version 6.01.3126,[14] with significant enhancements including GeoSPARQL in Open Source Edition 7.2.6, and in Enterprise Edition 8.2.0[15]
SpaceTime is a commercial spatiotemporal database built on top of the proprietary multidimensional index similar to the k-d tree family, but created using the bottom-up approach and adapted to particular space-time distribution of data.
^McKee, Lance (2016). "OGC History (detailed)". OGC. Retrieved 2016-07-12. [...] 1997 [...] OGC released the OpenGIS Simple Features Specification, which specifies the interface that enables diverse systems to communicate in terms of 'simple features' which are based on 2D geometry. The supported geometry types include points, lines, linestrings, curves, and polygons. Each geometric object is associated with a Spatial Reference System, which describes the coordinate space in which the geometric object is defined.
