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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.
An example of an OLAP cube. An OLAP cube is a multi-dimensional array of data. [1] Online analytical processing (OLAP) [2] is a computer-based technique of analyzing data to look for insights. The term cube here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than three.
The usual interface to manipulate an OLAP cube is a matrix interface, like Pivot tables in a spreadsheet program, which performs projection operations along the dimensions, such as aggregation or averaging. The cube metadata is typically created from a star schema or snowflake schema or fact constellation of tables in a relational database.
Local cubes, PowerPivot for Excel, Power BI Desktop: MicroStrategy Intelligence Server: Yes Yes Yes MicroStrategy Office, Dynamic Dashboards: Mondrian OLAP server: No Yes No Oracle Database OLAP Option: Yes No No SAP NetWeaver BW: Yes Yes No SAS OLAP Server: Yes Yes Yes StarRocks Yes Yes Yes Yes
Also note that of the above competitors, including Essbase, all use heterogenous relational (Microsoft SQL Server, Oracle, IBM DB/2, TeraData, Access, etc.) or non-relational data sourcing (Excel, text Files, CSV Files, etc.) to feed the cubes (facts and dimensional data), except for Oracle OLAP which may only use Oracle relational sourcing.
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.
OLAP cube; OLE DB for OLAP; Oracle OLAP; Oracle Retail Predictive Application Server; P. Palo (OLAP database) Panorama Software; ProClarity; S.
Feeding cubes – star schemas are used by all OLAP systems to build proprietary OLAP cubes efficiently; in fact, most major OLAP systems provide a ROLAP mode of operation which can use a star schema directly as a source without building a proprietary cube structure.