Spatial database

A spatial database is a database that is optimized for storing and querying data that represents objects defined in a geometric space. 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 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 geometry or feature data types. The Open Geospatial Consortium 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/EIC standard is a part the SQL/MM multimedia standard and extends the Simple Features standard with data types that support circular interpolations.[3]

Geodatabase

A geodatabase (also geographical database and geospatial database) is a database of geographic data, such as countries, administrative divisions, cities, and related information. Such databases can be useful for websites that wish to identify the locations of their visitors for customization purposes.

Features of spatial databases

Database systems use indexes to quickly look up values and the way that most databases index data is not optimal for spatial queries. Instead, spatial databases use a spatial index to speed up database operations.

In addition to typical SQL queries such as SELECT statements, spatial databases can perform a wide variety of spatial operations. The following operations and many more are specified by the Open Geospatial Consortium standard:

  • Spatial Measurements: Computes line length, polygon area, the distance between geometries, etc.
  • Spatial Functions: Modify existing features to create new ones, for example by providing a buffer around them, intersecting features, etc.
  • Spatial 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 which 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.

Spatial index

Spatial indices are used by spatial databases (databases which store information related to objects in space) to optimize spatial queries. Conventional index types do not efficiently handle spatial queries such as how far two points differ, or whether points fall within a spatial area of interest. Common spatial index methods include:

Spatial database systems

List

  • Open-source spatial databases and APIs, some of which are OpenGIS-compliant[4]
  • Caliper extends the Raima Data Manager with spatial datatypes, functions, and utilities.
  • Boeing's Spatial Query Server spatially enables Sybase ASE.
  • Smallworld VMDS, the native GE Smallworld GIS database
  • SpatiaLite extends Sqlite with spatial datatypes, functions, and utilities.
  • IBM DB2 Spatial Extender can spatially-enable any edition of DB2, including the free DB2 Express-C, with support for spatial types
  • Oracle Spatial
  • Oracle Locator[5]
  • Vertica Place, the geo-spatial extension for HP Vertica, adds OGC-compliant spatial features to the relational column-store database.[6]
  • Microsoft SQL Server has support for spatial types since version 2008
  • PostgreSQL DBMS (database management system) uses the spatial extension PostGIS to implement the standardized datatype geometry and corresponding functions.
  • Teradata Geospatial includes 2D spatial functionality (OGC-compliant) in its data warehouse system.
  • MonetDB/GIS extension for MonetDB adds OGS Simple Features to the relational column-store database.[7]
  • 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.[8] 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.
  • Neo4j – a graph database that can build 1D and 2D indexes as B-tree, Quadtree and Hilbert curve directly in the graph
  • AllegroGraph – a graph database which provides a mechanism for efficient storage and retrieval of two-dimensional geospatial coordinates for Resource Description Framework data. It includes an extension syntax for SPARQL queries.
  • RethinkDB supports geospatial indexes in 2D.
  • Esri has a number of both single-user and multiuser geodatabases.
  • CouchDB a document-based database system that can be spatially enabled by a plugin called Geocouch
  • H2 supports geometry types[9] and spatial indices[10] as of version 1.3.173 (2013-07-28). An extension called H2GIS available on Maven Central gives full OGC Simple Features support.
  • GeoMesa is a cloud-based spatio-temporal database built on top of Apache Accumulo and Apache Hadoop. GeoMesa supports full OGC Simple Features support and a GeoServer plugin.
  • Tarantool supports geospatial queries with RTREE index.[11]
  • SAP HANA supports geospatial with SPS08.[12]
  • Redis with the Geo API.[13]

Table of free systems especially for spatial data processing

DBSLicenseDistributedSpatial objectsSpatial functionsPostgreSQL interfaceUMN MapServer interfaceDocumentationModifiableHDFS
ESRI GIS Tools for Hadoop Apache License 2.0 yes yes (own specific API) yes (union, difference, intersect, clip, cut, buffer, equals, within, contains, crosses, and touches) no no just briefly forking yes
GeoMesa Apache License 2.0 yes yes (Simple Features) yes (JTS) no (manufacturable with GeoTools) no parts of the functions, a few examples with Simple Feature Access in Java Virtual Machine and Apache Spark are all kinds of tasks solvable yes
H2 (H2GIS) LGPL 3 (since v1.3), GPL 3 before no yes (custom, no raster) Simple Feature Access and custom functions for H2Network yes no yes (homepage) SQL no
Ingres GPL or proprietary yes (if extension is installed) yes (custom, no raster) Geometry Engine, Open Source[14] no with MapScript just briefly with C and OME no
Neo4J-spatial[15] GNU affero general public license no yes (Simple Features) yes (contain, cover, covered by, cross, disjoint, intersect, intersect window, overlap, touch, within and within distance) no no just briefly fork of JTS no
PostgreSQL with PostGIS GNU General Public License no yes (Simple Features and raster) yes (Simple Feature Access and raster functions) yes yes detailed SQL, in connection with R no
Postgres-XL with PostGIS Mozilla public license and GNU general public license yes yes (Simple Features and raster) yes (Simple Feature Access and raster functions) yes yes PostGIS: yes, Postgres-XL: briefly SQL, in connection with R or Tcl or Python no
Rasdaman server GPL, client LGPL, enterprise proprietary yes just raster raster manipulation with rasql yes with Web Coverage Service or Web Processing Service detailed wiki own defined function in enterprise edition no
RethinkDB AGPL yes yes
  • distance
  • getIntersecting
  • getNearest
  • includes
  • intersects
no no official documentation[16] forking no

See also

References

  1. 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.
  2. OGC Homepage
  3. (eds.), Wolfgang Kresse, David M. Danko (2010). Springer handbook of geographic information (1. ed.). Berlin: Springer. pp. 82–83. ISBN 9783540726807.
  4. Open Source GIS website
  5. Wei Li (2008). "2.1 Spatio-temporal Databases". An Efficient Query System for High-dimensional Spatio-temporal Data. ProQuest. p. 12. ISBN 9780549797593. Retrieved 2016-07-07. Commercial spatial database management systems include IBM DB2's Spatial Extender [42], Oracle's Spatial and Oracle Locator [66], and Microsoft's SQL Server 2008 [58], etc.
  6. "HP Vertica Place". 2 December 2015.
  7. "GeoSpatial – MonetDB". 4 March 2014.
  8. "Archived copy". Archived from the original on 2013-04-30. Retrieved 2013-05-01.
  9. H2 geometry type documentation
  10. H2 create spatial index documentation
  11. http://tarantool.org/doc/user_guide/RTREE.html#in-memory
  12. http://help.sap.com/hana/sap_hana_spatial_reference_en.pdf
  13. http://redis.io/commands/#geo
  14. http://trac.osgeo.org/geos/
  15. https://github.com/neo4j-contrib/spatial
  16. https://rethinkdb.com/api/javascript/

Further reading

  • Spatial Databases: A Tour, Shashi Shekhar and Sanjay Chawla, Prentice Hall, 2003 ( ISBN 0-13-017480-7)
  • ESRI Press. ESRI Press titles include Modeling Our World: The ESRI Guide to Geodatabase Design, and Designing Geodatabases: Case Studies in GIS Data Modeling , 2005 Ben Franklin Award winner, PMA, The Independent Book Publishers Association.
  • Spatial Databases – With Application to GIS Philippe Rigaux, Michel Scholl and Agnes Voisard. Morgan Kaufmann Publishers. 2002 ( ISBN 1-55860-588-6)
  • Evaluation of Data Management Systems for Geospatial Big Data Pouria Amirian, Anahid Basiri and Adam Winstanley. Springer. 2014 ( ISBN 9783319091563)
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