MOLAP
The first generation of server-based multidimensional OLAP (MOLAP) solutions use multidimensional databases (MDDBs). The main advantage of an MDDB over an RDBMS is that an MDDB can provide information quickly since it is calculated and stored at the appropriate hierarchy level in advance. However, this limits the flexibility of the MDDB since the dimensions and aggregations are predefined. If a business analyst wants to examine a dimension that is not defined in the MDDB, a developer needs to define the dimension in the database and modify the routines used to locate and reformat the source data before an operator can load the dimension data.
Another important operational consideration is that the data in the MDDB must be periodically updated to remain current. This update process needs to be scheduled and managed. In addition, the updates need to go through a data cleansing and validation process to ensure data consistency. Finally, an administrator needs to allocate time for creating indexes and aggregations, a task that can consume considerable time once the raw data has been loaded. (These requirements also apply if the company is building a data warehouse that is acting as a source for the MDDB.) Organizations typically need to invest significant resources in implementing MDDB systems and monitoring their daily operations. This complexity adds to implementation delays and costs, and requires significant IT involvement. This also results in the analyst, who is typically a business user, having a greater dependency on IT. Thus, one of the key benefits of this OLAP technology — the ability to analyze information without the use of IT professionals — may be significantly diminished.
Source: Business Insight Beyond OLAP - CorVu Corporation
http://www.corvu.com/library/whitepapers/beyondolap.html