Azure Databricks & Azure SQL Data Warehouse make an increasingly compelling pair as SQL DW hits new peaks of price-performance.

The foundation of any Cloud Scale Analytics platform must be based upon the ability to store and analyze data that may stretch traditional limits along any of the older “3 ‘V’s of Big Data: (Volume, Variety, Velocity), but realistically, must also excel with the fourth V: Value. Together, Azure Databricks and Azure SQL DW provide the most powerful 1-2 punch in the market across all 4 V’s.

With recent announcements, the Azure SQL Data Warehouse (DW) value proposition knocks its competitors out of the ring. Taken individually, Databricks and SQL Data Warehouse provide compelling, best-in-class tools for data storage, analysis, orchestration, security, and AI; taken as a platform, and weighted for total cost of ownership and price-performance, it’s hard to imagine looking elsewhere!

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Azure DW is now up to 14x faster and up to 94% cheaper than other major cloud DW solutions.
Read the Feb 2019 GigaOM report here.

Last year, when Microsoft and Databricks announced their ground-breaking partnership, they brought the de facto winner of the Big Data movement (Spark!) into Azure as a first-class PaaS offering, and at BlueGranite, we were practically shaking with excitement! Azure Databricks was a missing puzzle piece that fostered levels of integration, ease of use, and power (so much power!) and in combination with tools like Azure Data Factory and Azure SQL DW to create a singularly compelling platform for Cloud Scale Analytics. (New to that term? Learn why you should be getting on board here!)

At the time of the partnership announcement, cloud migrations were becoming cloud modernizations; organizations were leveraging the promise of the cloud to add new capabilities and levels of performance for data and analytics that were previously practically unavailable. On the heels of Azure Databricks becoming generally available, Azure SQL DW upped its game with new features that enabled greater customization of storage and compute, then landed at the top of the price-performance (P-P) ranking compared to its primary competitor. That was then: Read the Jul 2018 GigaOM benchmark report.

As organizations look to the cloud to enable Digital Transformation across their Data and AI efforts, both migrating and modernizing the existing DW environments and analytics becomes table stakes for any holistic strategy. And with another exponential improvement in P-P, Azure SQL DW is running away from the competition even before you consider all the complementary tools and features in Azure.  And on that last note, Microsoft is also announcing the general availability of Azure Data Lake Gen 2 and Azure Data Explorer. Along with Power BI for rich visualization, these support an enhanced set of capabilities that cements Microsoft’s leadership position in delivering Cloud Scale Analytics. Read the announcements here.

Now that we’ve covered Azure’s major advances and advantages, let’s take a moment to dig into what’s so exciting about employing it to modernize your organization’s Data and AI capabilities.

Azure SQL Data Warehouse offers availability of skill set, ease of deployment, seamless transition and adoption, exciting visualization, and virtually unlimited new capabilities… Not to oversell it, but that’s what is available when you leverage Azure for your Modern Data Platform!

And when it comes to taking advantage of new capabilities:

With all that power behind Azure SQL Data Warehouse and Azure Databricks, the possibilities are seemingly endless. If you’re ready to learn more about the Modern Data Platform or taking advantage of AI on Azure, take advantage of BlueGranite’s expertise below!

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