Multidimensional Online Analytical Processing (MOLAP) is a kind of online analytical processing (OLAP) that, like Relational Online Analytical Processing (ROLAP), uses a multidimensional data model to analyze data. Hybrid online analytical processing (HOLAP) is a combination of relational ROLAP and MOLAP.

In MOLAP, data is stored in a multidimensional semantic model. It has excellent performance and can do fast calculations.

In ROLAP, the data is stored in the relational database. It can handle large amounts of data and leverage functionalities inherent in the relational database. Query time can be longer if the underlying data size is large.

The difference between MOLAP and ROLAP is that MOLAP requires that information first be processed before it is indexed directly into a multidimensional semantic model, whereas ROLAP is entered directly into a relational database.

HOLAP uses a hybrid approach where as long as a query asks for materialized dimension or measure, it is served by the Kyvos Query Engines, but when a query asks for a non-materialized dimension or measures, it is served by delegating it to an external SQL Engine like PRESTO or Hive. This allows a user to design and process a semantic model but choose to keep some high cardinality dimensions or measures as non-materialized.

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