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?
Basically it comes down to the following:
A system that is really optimized for "in-memory" operations takes into account several aspects like random access, memory page size, different cache levels (CPU, ...) etc.
This leads to a maximum use of the possibilities that RAM offers and HDD does not offer which in turn makes for excellent performance.
A traditional engine which is optimized for filesystem access is usually taking into account several aspects relevant to files/OS handling of filesystem etc.
Even when such an engine loads everything into its cache (memory) it still operates on the data AS IF it were on disk which makes sense since the code must work in situations where not everything fits into memory too. Using the same implementation for both situation makes for better testing/stability/bug-fixing/maintainability etc. BUT this leads to "not taking advantage" of all that makes RAM access different from file/disk access. Such an engine usually can be made faster IF it implements RAM specific optimizations so that it offers in each world (RAM versus disk) the best ... I am not aware of any engine doing that ...
