Q:

What advantages does in-memory OLAP have over traditional systems with significant memory?

Do in-memory OLAP engines have advantages over the traditional OLAP engines backed by enough RAM to contain the entire cube(s)?
For example, if I use a MOLAP engine (SSAS) and GB / TB of RAM where the entire cube (or even star-schema) is RAM resident, what is the difference compared to something like TM1 / SAP HANA?

A:

Not my field of expertise but as I understand it the difference in the majority of so-called in-memory OLAP databases (not a term I'm fond of, it's used as marketing pitch more than as a fair comparison of technologies) is column store indexes.
Column-Stores vs Row-Stores (How Different Are They Really) is a good intro to the technology if you're familiar with traditional OLTP and OLAP database structures.

A:

Column store indexes will make an appearance in SQL Server 2012 (aka 'Denali').
Here is a link to a Power Point presentation by Conor Cunningham, Principal Software Architect in the SQL Server Query Processor team covering this new feature.

A:

Databases designed with the assumption that they will be entirely resident in main memory can use structures such as T-tree indexes. But the real advantage is, IMDBs are just simpler. They do less (as they don't have to worry about managing a cache, or serializing writes for consistency, or anything to do with ACID-compliant I/O at all) so they execute fewer instructions on the hardware to carry out the same "work". A general-purpose database has to be all things to all people; like a Leatherman has a dozen tools, but sometimes you just need a cutting edge, so you buy a blade from Cold Steel, and no-one debates that it is a better knife! 

