There is constant talk about big data; endless marketing decks, whitepapers, and blog posts about how fast data is multiplying on-premise and in the cloud. In many cases, familiar database technologies, such as Symmetric Multi-Processing (SMP) or “scale-up” architecture, can no longer process growing data sets fast enough for businesses to make timely decisions. Massively Parallel Processing (MPP) or “scale-out” architecture is quickly becoming the preferred alternative proven capable of handling larger (or massive) data sets.
Azure SQL Data Warehouse, or simply Azure SQL DW, allows companies to use MPP to take advantage of significant performance gains crunching large data sets without the investment and overhead of maintaining on-premise hardware and software. Simply provision an Azure SQL DW instance, and you gain access to all the advantages of MPP without the commitments of purchasing and maintaining the infrastructure associated with it. That noted, because Azure is a pay-as-you-go solution, it’s important to ensure you are as efficient as possible with those resources to get the most value from this platform-as-a-service (PaaS).