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In computing, online analytical processing, or OLAP (/ ˈ oʊ l æ p /), is an approach to quickly answer multi-dimensional analytical (MDA) queries. [1] The term OLAP was created as a slight modification of the traditional database term online transaction processing (OLTP). [2]
OLTP is often integrated into service-oriented architecture (SOA) and Web services. Online transaction processing (OLTP) involves gathering input information, processing the data and updating existing data to reflect the collected and processed information. As of today, most organizations use a database management system to support OLTP.
Since the early 1990s, the operational database software market has been largely taken over by SQL engines. In 2014, the operational DBMS market (formerly OLTP) was evolving dramatically, with new, innovative entrants and incumbents supporting the growing use of unstructured data and NoSQL DBMS engines, as well as XML databases and NewSQL databases.
Tableau Software originated at Stanford University as a government-sponsored research project to investigate new ways for users to interact with relational and OLAP databases. Hyperion and Tableau together built fundamentally the first versions of Tableau Software which was designed specifically for multidimensional (OLAP) databases.
The following tables compare general and technical information for a number of online analytical processing (OLAP) servers. Please see the individual products articles for further information. Please see the individual products articles for further information.
XML for Analysis (XMLA) is an industry standard for data access in analytical systems, such as online analytical processing (OLAP) and data mining. XMLA is based on other industry standards such as XML, SOAP and HTTP. XMLA is maintained by XMLA Council with Microsoft, Hyperion and SAS Institute being the XMLA Council founder members.
Multidimensional Expressions (MDX) is a query language for online analytical processing (OLAP) using a database management system. Much like SQL, it is a query language for OLAP cubes. [1] It is also a calculation language, with syntax similar to spreadsheet formulae.
With greater data demands among businesses, [citation needed] OLAP also has evolved. To meet the needs of applications, both technologies are dependent on their own systems and distinct architectures. [7] [6] As a result of the complexity in the information architecture and infrastructure of both OLTP and OLAP systems, data analysis is delayed.