AWS Redshift Performance versus SQL Multidimensional and Tabular cubes

This is an update to my recent blog AWS Redshift versus SQL Server cube. This performance benchmark includes SQL Server's Tabular cube technology, which wasn't possible as the in-memory database required more memory than available in the test server.
This updated benchmark includes

• AWS Redshift
• SQL Columnstore
• SQL Multidimensional Cube
• SQL Tabular Cube

The cubes were the slam dunk winners, which shouldn't surprise any Data Platform Architects. For many Data Platform Architects, this will validate their use of columnar databases for atomic data combined with an OLAP cube for fast and scalable BI queries.

The races within the race were interesting. With Multidmensional beating Tabular by a factor of two, and SQL Columnstore beating AWS Redshift by a factor of two also.

For the full report goto AWS Redshift versus OLAP Cubes Performance Benchmark AWS Redshift versus OLAP cubes: Performance Benchmark.

AWS Redshift versus SQL Server cube

Here is a straight out performance benchmark between AWS' Redshift, SQL Server cube, and SQL Server columnstore indexing. If you are choosing between these (and potentially other) platforms, this will provide some interesting reading. 
Essentially, the Microsoft cube was 97% faster than Redshift.

Note, I tried to make the test as independent and representative of a retail enterprise's query load as possible. The underlying fact tables contained 100 million, 430 million and 600 million rows. The queries ranged from the banal to common calcs such as "year to date" and "stock days on hand".

If you are serious about making the right decision for your organisation, you might set up a similar test with your own data and popular queries. 

Here is the full report:
Data Platform Performance Paper

This benchmark has been updated to include SQL Tabular cube performance. Here is the updated paper.