I get many inquiries on the differences and pros and cons of MOLAP versus ROLAP architectures for analytics and BI. In the old days, the differences between MOLAP, DOLAP, HOLAP, and ROLAP were pretty clear. Today, given the modern scalability requirements, DOLAP has all but disappeared, and the lines between MOLAP, ROLAP, and HOLAP are getting murkier and murkier. Here are some of the reasons:
Some RDBMSes (Oracle, DB2, Microsoft) offer built-in OLAP engines, often eliminating a need to have a separate OLAP engine in BI tools.
Some of the DW-optimized DBMSes like Teradata, SybaseIQ, and Netezza partially eliminate the need for an OLAP engine with aggregate indexes, columnar architecture, or brute force table scans.
MOLAP engines like Microsoft SSAS and Oracle Essbase can do drill-throughs to detailed transactions.
Semantic layers like SAP BusinessObjects Universe have some OLAP-like functionality.