Multidimensional database

Multidimensional databases are variously (depending on the context) data aggregators which combine data from a multitude of data sources; databases which offer networks, hierarchies, arrays and other data formats difficult to model in SQL; or databases which give a high degree of flexibility in the definition of dimensions, units, and unit relationships, regardless of data format.

Multi-dimensional databases are especially useful in a sales and marketing applications that involve time series. Large volumes of sales and inventory data can be stored to ultimately be used for sales and executive planning. For example, data can be more readily segregated by sales region, product, or time period. While many of the major database vendors have made acknowledged the need for the this type of product offering, most frequently they rely upon a Star database design. However, The Star database design does not account for "sparse data" thereby not as efficiently improving the performance of database reporting. Accounting for sparse data eliminates large blocks of empty placeholders and improves the performance of the database as a whole.

This is an active area of database development, in which the set of desired features is somewhat vague, but better-defined than the set of known or proposed solutions. Defining and implementing a database which allows people at each level of an organization to define tables and data formats in the way that is most useful to them, yet which supports a single clear query language and consistent infrastructure, remains an open problem.

Examples

• Pick operating system
• OpenQM
• RealityX
• Caché
• GT.M
• U2 suite
• UniVerse and UniData
• OLAP versions of many major databases, such as MDX
• Microsoft Analysis Services
• Oracle
• Hyperion's Essbase
• Mumps compiler
• Multidimensional hierarchical toolkit
• Open source olap
• [[Pilot Software(Cambridge, MA USA) Time Series Database Server from 1990

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External links

• PickWiki - Wiki about Multidimensional databases