Array DBMS: Difference between revisions

Revision as of 07:01, 19 September 2014

Revision as of 11:00, 25 October 2014

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Array databases aim at offering flexible, scalable storage and retrieval on this information category.

[[ImageFile:Euclidean neighborhood in n-D arrays.png|thumb|150px|alt=Euclidean neighborhood of elements in arrays|Euclidean neighborhood of elements in arrays]]

== Overview ==

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The following are representative domains in which large-scale multi-dimensional array data are handled:

* Earth sciences: geodesy / mapping, remote sensing, geology, oceanography, hydrology, atmospheric sciences, cryospheric sciences

* Space sciences: Planetary sciences, astrophysics (optical and radio telescope observations, cosmological simulations)

* Life sciences: gene data, confocal microscopy, CAT scans

* Social sciences: statistical data cubes

* Business: OLAP, data warehousing

These are but examples; generally, arrays frequently represent sensor, simulation, image, and statistics data.

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== List of Array DBMS ==

* [[GeoRaster|Oracle GeoRaster]]

* [[MonetDB]]

* [[PostGIS]]

* [[rasdaman]]

* [[SciDB]]

== See also ==

*[[Data Intensive Computing]]

== References ==

{{Reflist}}

== See also ==

[[Data Intensive Computing]]

{{Database models}}