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New Releases for the Microsoft Data Platform


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The Microsoft data platform team is on fire! They are delivering more updates and features faster and more thoroughly than ever before. If you’re a data professional and you’re using the Microsoft stack, this is a really exciting time to be involved. They are innovating at the most rapid rate I’ve ever seen for a data management products company. They’re passionate. They’re motivated. And they’re communicating on a daily basis with their customers to ensure that they’re delivering the greatest amount of value.

SQL Server 2016 Public Preview

SQL Server 2016 continues to push deep innovations into their flagship database management system, as both an on-premises RDBMS, a hybrid platform, and a strictly cloud platform. Top new capabilities for this release include:

  • Stretch Database: a new technology that lets you dynamically stretch your warm and cold transactional data into the Microsoft Azure cloud. (I wrote about stretch databases back in www.dbta.com/Columns/SQL-Server-Drill-Down/StretchDB-a-Cool-New-Feature-in-vNext-SQL-Server-102971.aspx).
  • Always Encrypted: a new transparent security capability that protects data at rest and in motion, providing a greater degree of security than the Transparent Data Encryption (TDE) feature of earlier releases.
  • Further enhancements to the In-Memory OLTP technologies, also known as “Hekaton,” for real-time analytics on top of very high-speed transactional performance at approximately 30x faster processing speeds than traditional OLTP workloads. The new in-memory columnstore indexes can speed certain workflows by over 100x.
  • All new in-database analytics that integrate R programming language.
  • In addition, the Azure SQL Database platform has added features for row-level security and dynamic data masking.

For more information, you can:

SSIS Feature Packs For Azure Now Available

One of the long-standing differentiators between Microsoft SQL Server and other major RDBMS vendors is that Microsoft includes all of their product offerings within a given SQL Server licenses. So where you would have to pay for separate licenses for data warehousing or ETL products on other commercial DBMSes, they all come in the box with SQL Server. One such example is SQL Server Integration Services (SSIS). SSIS is a high-end data movement engine for Extract-Transform-Load (ETL) workloads.

Microsoft has released two new SSIS Feature Packs for Azure, one for SQL Server 2014 and another for SQL Server 2012, to provide the capability of connecting to and moving data between on-premises databases and cloud-based Azure Blob Storage and Azure HDInsight nosql data stores. The feature packs also provide features like creating or dropping HDInsight Hadoop clusters, invoking Hive or Pig jobs on the HDInsight cluster, and performing Foreach loop operations on multiple blob files in Azure Blog Storage.

Get the Microsoft SQL Server 2014 SSIS Feature Pack for Azure at www.microsoft.com/en-us/download/details.aspx?id=47366, while the SQL Server 2012 SSIS Feature Pack for Azure is located at www.microsoft.com/en-us/download/details.aspx?id=47367.

There’s also a nice set of user documentation for the feature packs at msdn.microsoft.com/en-US/library/mt146770.aspx.

The Azure SQL Data Warehouse

Microsoft has long offered data warehousing and multi-dimensional data processing through the SQL Server Analysis Services (SSAS) engine. Now, customers can get the full range of data warehousing features entirely online. Customers pay only for their Azure blog storage, data egress, and hourly compute rates, all while offering the traditional cloud advantage of elastic storage and computing resources. Basically, you pay for what you need, when you need it.

There are a LOT of features and capabilities available through the Azure SQL Data Warehouse. Your best bet is to study the offering more deeply by reading at http://azure.microsoft.com/en-us/campaigns/sql-data-warehouse/. You’ll find the full complement of pricing information, documentation, support info and so on.


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