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.
I get lots of questions from clients on whether they should consider (or continue to rely on) SAP BW for their data warehousing (DW) and business intelligence (BI) platform, tools, and applications. It’s a multidimensional (forgive the pun) decision. Jim Kobielus and I authored our original point of view on the subject soon after the SAP/BusinessObjects merger, so this is an updated view. In addition to what I’ll describe here, please also refer to all of the DW research by my colleague, Jim Kobielus.
First of all, split the evaluation and the decision into two parts: front end (BI) and back end (DW).
Back end – DW
Best for SAP-centric environments.
Agile tool that lets you control multiple layers (typically handled by different tools) such as ETL, DDL, metadata, SQL/MDX from a single administrative interface.