In April we announced the general availability of Azure Analysis Services, which evolved from the proven analytics engine in Microsoft SQL Server Analysis Services. The success of any modern data-driven organization requires that information is available at the fingertips of every business user, not just IT professionals and data scientists, to guide their day-to-day decisions. Self-service BI tools have made huge strides in making data accessible to business users. However, most business users don’t have the expertise or desire to do the heavy lifting that is typically required, including finding the right sources of data, importing the raw data, transforming it into the right shape, and adding business logic and metrics, before they can explore the data to derive insights. With Azure Analysis Services, a BI professional can create a semantic model over the raw data and share it with business users so that all they need to do is connect to the model from any BI tool and immediately explore the data and gain insights. Azure Analysis Services uses a highly optimized in-memory engine to provide responses to user queries at the speed of thought.
Today we are introducing two new SKU sizes, the S8 and S9 allowing you to build data models up to 400 GB in size.
The S8 offers up to 200 GB of cache with 320 QPUs, while the S9 offers up to 400 GB of cache and 640 QPUs. The cache sizes refer to the size of the memory to hold data in after it has been compressed. You do need to reserve some cache for processing and querying. A Query Processing Unit (QPU) in Azure Analysis Services is a unit of measure for relative computational performance for query and data processing. As a rule of thumb, one virtual core approximates to roughly 20 QPUs, although the exact performance depends on the underlying hardware and the generation of hardware used.
The new S8 and S9 SKUs are currently only available in the East US 2 and West Europe datacenters. To learn more about pricing for S8 and S9, please visit our pricing page.