Massive parallel processing (MPP) is the future for data warehousing.
So what is MPP? SQL Server is a Symmetric Multiprocessing (SMP) solution, which essentially means it uses one server. MPP provides scalability and query performance by running independent servers in parallel. That is the quick definition. For more details, read What MPP means to SQL Server Parallel Data Warehouse.
Microsoft has an MPP appliance called the Analytics Platform System (APS). If you are building a new data warehouse that will be of any decent size in the next few years (i.e. 1TB or greater), it is really a “no brainer” to purchase a MPP solution over a SMP solution,
Looking at the value over time for a MPP appliance vs a SMP solution:
The financial metrics of the two approaches were overwhelmingly in favor of the Big Data Solution (MPP) approach:
The bottom line is that for big data projects, the traditional data warehouse approach is more expensive in IT resources, takes much longer to do, and provides a less attractive return-on-investment.
Getting into the specific reasons to choose MPP (i.e. APS) over SMP when building a data warehouse:
If you are currently housing a data warehouse on SMP, it will almost always be worth the migration effort to switch to a MPP solution. Remember that old saying: “pay me know or pay me later”!
But there are some reasons where MPP may not be a good fit or should be supplemented with a SMP solution and/or a SSAS cube:
Another benefit is APS is an appliance solution, meaning it is prebuilt with software, hardware, and networking components already installed. Think of it as “Big data in a box”. Some of the appliance benefits:
Financial Comparison of Big Data MPP Solution and Data Warehouse Appliance