OLAP, ROLAP, MOLAP, and HOLAP

Online analytical processing (OLAP) systems--which have their rootsin decision support systems (DSSs) and executive information systems(EISs)--store data in multidimensional databases. You then access the databasesto perform financial and statistical analyses on different combinations of thedata. OLAP products are particularly useful for time-series analyses andrecursive calculations.

Vendors offer a variety of OLAP products that you can group into threecategories: relational OLAP (ROLAP), multidimensional OLAP (MOLAP), and hybridOLAP (HOLAP). ROLAP products (e.g., Informix's MetaCube ROLAP Option for theInformix Dynamic Server, MicroStrategy's DSS Agent) adapt traditional relationaldatabases to support OLAP. Vendors often use a star schema structure to extendand adapt an underlying relational database as an OLAP server.

MOLAP products (such as Arbor Software's Arbor Essbase OLAP Server 5 andOracle's Oracle Express Server) provide multi-dimensional analyses of data byputting data in a cube structure. Most successful MOLAP products use a multicubeapproach in which a series of small, dense, precalculated cubes make up ahypercube.

HOLAP products (e.g., Microsoft SQL Server OLAP Services and PilotSoftware's Pilot Decision Support Suite) combine MOLAP and ROLAP. With HOLAPproducts, a relational database stores most of the data. A separatemulti-dimensional database stores the most dense data, which is typically asmall proportion of the data.