In-database processing: Difference between revisions

Revision as of 08:14, 11 March 2013

Revision as of 08:33, 19 March 2013

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==History==

Traditional approaches to data analysis require data to be moved out of the database into a separate analytics environment for processing, and then back to the database. ([[SAS (software)|SAS]] and [[SPSS]] from [[IBM]] are examples of tools that still do this today.) Doing the analysis in the database, where the data resides, eliminates the costs, time and security issues associated with the old approach by doing the processing in the data warehouse itself.<ref name="DBTA">{{citation|last=Das|first=Joydeep|title=Adding Competitive Muscle with In-Database Analytics|url=http://www.dbta.com/Articles/Editorial/Trends-and-Applications/Adding-Competitive-Muscle-with-In-Database-Analytics-67126.aspx|publisher=Database Trends & Applications|date=May 10, 2010}}</ref>

Though in-database capabilities were first commercially offered in the mid-1990s, as object-related database systems from vendors including IBM, [[Illustra]]/[[Informix]] (now IBM) and [[Oracle Corporation|Oracle]], the technology did not begin to catch on until the mid-2000s.<ref name="IE">{{citation|last=Grimes|first=Seth|title=In-Database Analytics: A Passing Lane for Complex Analysis|url=http://intelligent-enterprise.informationweek.com/info_centers/data_int/showArticle.jhtml;jsessionid=YH5ZICM4SKOMRQE1GHPSKH4ATMY32JVN?articleID=212500351&cid=RSSfeed_IE_News|publisher=Intelligent Enterprise|date=December 15, 2008}}</ref>

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==Vendors==

In-database processing is performed and promoted as a feature by many of the major data warehousing vendors, including [[Teradata]] (and acquired [[Aster Data Systems]]), IBM [[Netezza]], EMC [[Greenplum]], [[Sybase]] and SAS [[SybaseSAS® In-Database]].

==Related Technologies==