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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.
Apache Kylin is a distributed data store for OLAP queries originally developed by eBay. Cubes (OLAP server) is another lightweight open-source toolkit implementation of OLAP functionality in the Python programming language with built-in ROLAP. ClickHouse is a fairly new column-oriented DBMS focusing on fast processing and response times.
Cubes is a light-weight open source multidimensional modelling and OLAP toolkit for development reporting applications and browsing of aggregated data written in Python programming language released under the MIT License.
Data processing, management and performance related features: OLAP server Real Time Write-back ... OLAP server # cubes # measures # dimensions # dimensions in cube
In computer programming contexts, a data cube (or datacube) is a multi-dimensional ("n-D") array of values. Typically, the term data cube is applied in contexts where these arrays are massively larger than the hosting computer's main memory; examples include multi-terabyte/petabyte data warehouses and time series of image data.
The MultiDimensional eXpressions (MDX) language provides a specialized syntax for querying and manipulating the multidimensional data stored in OLAP cubes. [1] While it is possible to translate some of these into traditional SQL, it would frequently require the synthesis of clumsy SQL expressions even for very simple MDX expressions.
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.
Holos Server provided an array of different, but compatible, storage mechanisms for its multi-cube architecture: memory, disk, SQL. It was therefore the first product to provide "hybrid OLAP" . The Holos Client was both a design and delivery vehicle, and this made it quite large.