Editing Online analytical processing (section)

==Products==

===History===
The first product that performed OLAP queries was ''Express,'' which was released in 1970 (and acquired by [[Oracle Corporation|Oracle]] in 1995 from Information Resources).<ref>{{cite web|title=The origins of today's OLAP products |url=http://olapreport.com/origins.htm |publisher=OLAP Report |date=2007-08-23 |author=Nigel Pendse |access-date=November 27, 2007 |url-status=usurped |archive-url=https://web.archive.org/web/20071221044811/http://www.olapreport.com/origins.htm |archive-date=December 21, 2007 }}</ref> However, the term did not appear until 1993 when it was coined by [[Edgar F. Codd]], who has been described as "the father of the relational database". Codd's paper<ref name=Codd1993/> resulted from a short consulting assignment which Codd undertook for former Arbor Software (later [[Hyperion Solutions]], and in 2007 acquired by Oracle), as a sort of marketing coup. 

The company had released its own OLAP product, ''[[Essbase]]'', a year earlier. As a result, Codd's "twelve laws of online analytical processing" were explicit in their reference to Essbase. There was some ensuing controversy and when Computerworld learned that Codd was paid by Arbor, it retracted the article. The OLAP market experienced strong growth in the late 1990s with dozens of commercial products going into market. In 1998, Microsoft released its first OLAP Server{{snd}} [[Microsoft Analysis Services]], which drove wide adoption of OLAP technology and moved it into the mainstream.

===Product comparison===
{{Main|Comparison of OLAP servers}}

===OLAP clients===
OLAP clients include many spreadsheet programs like Excel, web application, SQL, dashboard tools, etc. Many clients support interactive data exploration where users select dimensions and measures of interest. Some dimensions are used as filters (for slicing and dicing the data) while others are selected as the axes of a pivot table or pivot chart. Users can also vary aggregation level (for drilling-down or rolling-up) the displayed view. Clients can also offer a variety of graphical widgets such as sliders, geographic maps, heat maps and more which can be grouped and coordinated as dashboards. An extensive list of clients appears in the visualization column of the [[comparison of OLAP servers]] table.

===Market structure===
Below is a list of top OLAP vendors in 2006, with figures in millions of [[US Dollar]]s.<ref>{{cite web
  |url=http://www.olapreport.com/market.htm
  |archive-url=https://web.archive.org/web/19970330103741/http://www.olapreport.com/MARKET.HTM
  |url-status=usurped
  |archive-date=March 30, 1997
  |title=OLAP Market
  |publisher=OLAP Report
  |author=Nigel Pendse
  |year=2006
  |access-date=2008-03-17
}}</ref>
{| class="wikitable sortable"
! Vendor !! Global Revenue  !! Consolidated company
|-
| [[Microsoft Corporation]] || 1,806   || Microsoft
|-
| [[Hyperion Solutions Corporation]] || 1,077  || Oracle
|-
| [[Cognos]] || 735  || IBM
|-
| [[Business Objects (company)|Business Objects]] || 416 || SAP
|-
| [[MicroStrategy]] || 416 || MicroStrategy
|-
| [[SAP AG]] || 330 || SAP
|-
| Cartesis ([[SAP AG|SAP]]) || 210  || SAP
|-
| [[Applix]] || 205  || IBM
|-
| [[Infor]] || 199  || Infor
|-
| [[Oracle Corporation]] || 159 || Oracle
|-
| Others || 152  || Others
|-
| '''Total''' || '''5,700'''
|}

=== Open source ===
*[[Apache Pinot]] is used at LinkedIn, Cisco, Uber, Slack, Stripe, DoorDash, Target, Walmart, Amazon, and Microsoft to deliver scalable real time analytics with low latency.<ref>{{cite news |last= Yegulalp |first=Serdar |date=2015-06-11 |title= LinkedIn fills another SQL-on-Hadoop niche |url=http://www.infoworld.com/article/2934506/olap/linkedins-pinot-fills-another-sql-on-hadoop-niche.html |magazine=InfoWorld |access-date=2016-11-19}}</ref> It can ingest data from offline data sources (such as Hadoop and flat files) as well as online sources (such as Kafka). Pinot is designed to scale horizontally.
* [[Mondrian OLAP server]] is an [[open-source software|open-source]] OLAP server written in [[Java (programming language)|Java]]. It supports the [[Multidimensional Expressions|MDX]] query language, the [[XML for Analysis]] and the {{usurped|1=[https://web.archive.org/web/20150312031439/http://www.olap4j.org/ olap4j]}} interface specifications.
* Apache Doris is an open-source real-time analytical database based on MPP architecture. It can support both high-concurrency point query scenarios and high-throughput complex analysis.<ref>{{cite web |title=Apache Doris |url=https://github.com/apache/doris |website=Github |publisher=Apache Doris Community |access-date=5 April 2023}}</ref> 
* [[Apache Druid]] is a popular open-source distributed data store for OLAP queries that is used at scale in production by various organizations.
* [[Apache Kylin]] is a distributed data store for OLAP queries originally developed by eBay.
* [[Cubes (OLAP server)]] is another lightweight [[open-source software|open-source]] toolkit implementation of OLAP functionality in the [[Python (programming language)|Python programming language]] with built-in ROLAP.
* [[ClickHouse]] is a fairly new column-oriented DBMS focusing on fast processing and response times.
* [[DuckDB]]<ref>{{Cite web |title=An in-process SQL OLAP database management system |url=https://duckdb.org/ |access-date=2022-12-10 |website=DuckDB |language=en}}</ref> is an in-process SQL OLAP<ref>{{Cite web |last=Anand |first=Chillar |date=2022-11-17 |title=Common Crawl On Laptop - Extracting Subset Of Data |url=https://avilpage.com/2022/11/common-crawl-laptop-extract-subset.html |access-date=2022-12-10 |website=Avil Page |language=en}}</ref> database management system.
* [[MonetDB]] is a mature open-source column-oriented SQL RDBMS designed for OLAP queries.