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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.
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]
This is a comparison of object–relational database management systems (ORDBMSs). Each system has at least some features of an object–relational database ; they vary widely in their completeness and the approaches taken.
It is similar to a database management system (DBMS), which is, however, designed for static data in conventional databases. A DBMS also offers a flexible query processing so that the information needed can be expressed using queries. However, in contrast to a DBMS, a DSMS executes a continuous query that is not only performed once, but is ...
Druid is commonly used in business intelligence-OLAP applications to analyze high volumes of real-time and historical data. [4] Druid is used in production by technology companies such as Alibaba , [ 4 ] Airbnb , [ 4 ] Nielsen , [ 4 ] Cisco , [ 5 ] [ 4 ] eBay , [ 6 ] Lyft , [ 7 ] Netflix , [ 8 ] PayPal , [ 4 ] Pinterest , [ 9 ] Reddit , [ 10 ...
As of Oracle Database 11g, the Oracle database optimizer can transparently redirect SQL queries to levels within the OLAP Option cubes. The cubes are managed and can take the place of multi-dimensional materialized views, simplifying Oracle data-warehouse management and speeding up query response.
The term "transaction" can have two different meanings, both of which might apply: in the realm of computers or database transactions it denotes an atomic change of state, whereas in the realm of business or finance, the term typically denotes an exchange of economic entities (as used by, e.g., Transaction Processing Performance Council or commercial transactions.
Databases made it then possible to develop languages that made it easy to produce reports for retrospective analytics. At about the same time, languages and systems were developed to handle multidimensional data and to automate mathematical techniques for forecasting and optimization as part of prospective analytics.