MOLAP

MOLAP, or Multidimensional Online Analytical Processing, is a category of OLAP technology that stores and manages data in multidimensional cubes rather than in flat relational tables. In a MOLAP system, data is organized across multiple dimensions such as time, geography, product, and customer, with measures like sales, quantity, and profit. The cube structure enables fast execution of analytical operations by aggregating data along predefined hierarchies.

Storage and processing in MOLAP involve loading data from a data warehouse into the MOLAP cube, where it is pre-aggregated and often compressed. The engine maintains a dense, multi-dimensional index that supports rapid retrieval of aggregated values. Because much of the computation occurs at build time, queries that request complex aggregations can be answered with minimal on-demand processing.

MOLAP is typically very fast for read-heavy analytical queries, especially when they align with the cube’s dimensions and hierarchies. It is well suited for dashboards and scorecards that require consistent, immediate results. However, MOLAP can face scalability and maintenance challenges as the number of dimensions and distinct values grows, since larger cubes require more storage and more complex update processes.

Compared with other OLAP models, MOLAP stores data in specialized internal structures rather than in relational tables, which differentiates it from ROLAP and HOLAP. MOLAP tends to be less flexible for ad hoc analysis on very large, high-cardinality datasets. Many BI platforms offer MOLAP storage modes, illustrating its continued use in enterprise analytics alongside other OLAP approaches.