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What is Azure SQL Data Warehouse?

Azure SQL Data Warehouse transforms the way you access and manage data to drive business results. For those in the financial services industry, this can make a big difference to both your bottom line and the efficiency of business-critical applications.

Let’s take a look at how Azure SQL Data Warehouse works and why 46 percent of organisations are moving data into the cloud.



What is Azure SQL Data Warehouse and how does it work?

Azure SQL Data Warehouse is a massively parallel-processing database run in the Microsoft Cloud. Its job is to spread your data across multiple shared storage and processing units, before handling the logic involved in data queries.

Because of this, it's well suited to the batch loading, transformation, and serving of huge volumes of data. As an integrated Azure feature, the Data Warehouse offers the same scalability and continuity as other Azure services such as high-performance computing.

At an infrastructure level, each Data Warehouse is made up of:

  • Storage – Azure Premium Disk Storage, which is internally managed by the compute node. You can also attach Azure Storage Blobs as external tables.
  • A control node – manages and optimises queries to run in parallel on separate compute nodes, returning aggregated results to the client application.
  • Compute nodes – SQL databases that store data and process queries, returning results to the control nodes.

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What can Azure SQL Data Warehouse do for my organisation?

If you’re wondering how SQL Data Warehouse can work for your organisation, here’s a few use case examples:

  • Ingesting and batch processing persistent storage such as Azure Storage Blobs, HDFS and Azure Data Lake Store
  • Serving stored data to intelligence services such as Azure Cognitive Services or Azure Machine Learning
  • Serving data to analytics clients such as Power BI, Tableau, Excel, APIs etc.

You might also consider these alternative technologies depending on your specific requirements:

  • For batch processing: Azure Batch, Spark/Hive, Azure data Lake Analytics
  • For serving storage: Azure Document DB, Azure SQL DB, Azure redis Cache, HBase, Azure Search, Azure Analysis Services

Data on-demand

What's unique about SQL Data Warehouse - especially in a batch processing context - is that you can pause and resume the control and compute nodes while keeping your data in storage.

Decoupling storage and compute means you only pay for the service you’re using, saving you money and making it easier to scale either independently. Doing this enables you to:

  • Increase or reduce storage without affecting compute
  • Increase or reduce compute without moving data
  • Pause compute without losing storage data
  • Resume compute at any time

As well as increased scalability, accessing data in this way reduces the operational cost of continuously running SQL databases. Other benefits of Azure SQL Data Warehouse include:

  • Real or near-real time querying (ensured by optimised parallel processing)
  • External dataset querying in SQL with PolyBase
  • Microsoft-standard security and regulatory compliance
  • Simplified disaster recovery with geo-redundant backups

Getting more from SQL Azure


The professional services industry generated nearly 40 percent of the world’s big data revenue in 2014 and we only expect this segment of the market to carry on growing.

If you’re looking to use big data more effectively in your business through familiar SQL constructs, then Azure SQL Data Warehouse is the best place to start.

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