MOLAP is a type of on-line analytical processing methodology that is quite popular in the business intelligence world.

How It Works

The “M” stands for multidimensional. From a technology standpoint, it basically means that the data is stored in a “cube” like fashion. The software takes the datasource and transforms it into the necessary data structure for the technology to handle queries, analysis, etc… The transformation typically does all of the necessary calculations and pre-aggregations so all of that data is available quickly for end users. Ususually little or no additional SQL would need to be run. In some instances, the data may be stored in-memory, which can also aid performance as that is much quicker than running from a disk, and no additional data warehouse usage is necessary.

In the right context, this technology can be an excellent addition to a BI implementation. Generally, they are best for implementations for smaller data requirements (under 100gb) and a reasonable amount of dimensions.

Pros and Cons

This has several advantages:

Calculations can be done ahead of time to speed performance when querying

Aggregates can be pre-calculated

The structure can be smaller than a corresponding RDMS structure in terms of disk space

Excellent for data sets with only a few dimensions

However with this technology come several disadvantages:

A structure to pre-process the data and calculations can be time and resource intensive

Datasets with many dimensions can rapidly drop performance

Data with high numbers of transactions can be slow to query


Several of the major vendors have a MOLAP technology available.

Cognos TM1 – One of the leaders with this technology. It’s proven especially popular in the planning and forecasting fields.

Microsoft Analysis Services – Along with Cognos is one of the more popular cube options.

Several other smaller vendors including PowerOLAP have had products in the past.

Palo is an interesting open source option that offers a multidimensional component

Go to OLAP from MOLAP

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