Microsoft targets AWS Redshift and New Azure SQL Data Warehouse

Microsoft was clear about who its new Azure SQL Data Warehouse was aimed at during yesterday’s keynote address at the Build developer conference.
Scott Guthrie, an executive, stated that there are “other data warehouse offerings on the market today” and pointed out that Amazon Web Services Inc.’s Redshift offering has seen “good uplift.” Guthrie said, “I want a little more time now talking about Azure being even better” and posted a slide showing the benefits.
[Click on the image to see a larger view.] Azure SQL Data Warehouse vs. AWS Redshift. (source: Microsoft). Azure SQL Data Warehouse will be available for preview in June. It was designed to offer petabyte-scale data warehouses as a service that can adapt to business needs. The AWS Redshift, which was unveiled over two years ago, is described as “a fast and fully managed, petabyte scale data warehouse solution that makes analyzing all your data easy and cost-effective using your existing business intelligence tools.”
Guthrie yesterday highlighted the many advantages that Azure SQL Data Warehouse offers over AWS Redshift. He said that Azure SQL Data Warehouse allows you to adjust compute and storage independently, rather than Redshift’s fixed compute/storage ratio. Microsoft’s new service is described as “the first enterprise-class cloud storage warehouse” and can grow, shrink, and pause in seconds. Redshift could take hours, if not days, to resize. Guthrie stated that Azure SQL Data Warehouse offers hybrid configuration options for hosting in the Azure cloud and on-premises. This allows for pause/resume functionality, compatibility with real SQL queries, and can be used to host Redshift services. Redshift does not support stored procedures, constraints, indexes or SQL UDFs.
[Click on the image to see a larger version.] Introducing SQL Data Warehouse (source : Microsoft). Enterprises can use this new offering in conjunction other Microsoft data tools, such as PowerBI (data visualization), Azure Machine Learning(advanced analytics), AzureHDInsight (managed Apache Hadoop big data service), and Azure Data Factory (data orchestration).
T.K., an executive, stated that Azure SQL Data Warehouse is built on the massively parallel processing architecture available in SQL Server and the Analytics Platform System Appliance. “Ranga” Rengarajan in a blog post yesterday.
Microsoft also introduced several data-related products yesterday. These included the Azure SQL Database elastic databases, and the Azure Data Lake. Rengarajan stated that the former will allow you to create SaaS applications that can manage large databases with unpredictable resource demands. The latter was designed to overcome limitations in traditional analytics infrastructure and realize the idea for a data lake’ — a single location to store all types of data in their native format, with no fixed limits on file size or account size, high throughput to improve analytic performance, and native integration with Hadoop ecosystem. You can find more information here.

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