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Faster Cloud Warehouses

By Steve Jones,

I think the cloud is a perfect place for a data warehouse. In many organizations, I've found that a data warehouse system is often the largest SQL Server database, both in size of database and also in terms of resources allocated. These systems often handle many complex queries for business users and are allocated a large number of CPUs as well as lots of RAM. Even then, many ad hoc BI tools or lots of "what-if" queries can bring the system to its knees, often causing lots of stress for database administrators during the periods of time when the system is in heavy use.

Fortunately, many of these systems aren't in use all the time. Often these are systems used by financial departments to "close the books" at month, quarter, or year end. It's at these times when lots of resources are needed. Outside of these times, the data warehouse might be one of the least used systems, which makes it a perfect choice for a cloud, scale on demand, environment. Scale up when needed, down when not, limit your costs to the resources you need, when you need them.

Microsoft has increased the capabilities of the Azure SQL Data Warehouse quite a few times across the last few years. I was thrilled to see ASDW separate out storage from compute, allowing customers to scale up the query, or compute, nodes independently of the storage used. Changes last year improved the ability to move data around between compute nodes as well as increased the number of concurrent queries. 

These improvements are perfect for data warehouses, and if you are looking to build a more responsive SQL Server based warehouse, you ought to take a look at ASDW. More and more customers are finding it valuable and cost effective in their businesses. What seemed to once be a niche idea has grown into a business that quite a few customers are using, with the demand growing.

What's more, the move to Big Data Clusters in SQL Server 2019 seems to have adapting some of this technology to the regular SQL Server product many of us use. These will separate out the storage from compute, something that should help many of us scale our systems to meet the demand of our workloads. I haven't tried a big data cluster yet, but I'm looking forward to seeing how well one works and if it truly scales SQL Server further than I would have dreamed.

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