SQL Server 2016: Broader Access, Better Reporting, Faster Analytics

Datetime:2016-08-23 02:28:45          Topic: SQL Server           Share

Microsoft wants to make it easier for businesses to use their data. Otherwise, what’s the point? In SQL Server 2016 you’ll find a virtual tool chest full of features, all with one primary goal: unlocking your data and helping you create new ways of analyzing, visualizing and sharing it.

Building data-rich biz apps

The advent of machine learning and natural language processing made it easier to analyze unstructured data. The challenge was effectively integrating it with structured data, leading to more meaningful discoveries.

Enter SQL Server PolyBase, a feature in SQL Server 2014 that was specific to the Microsoft Analytics Platform System, through which you could access data in a Hadoop Distributed File System. With SQL Server 2016 we cut the strings, making it possible to query data in Hadoop, as well as Azure Blob Storage. Now you can combine the results of your findings with relational data stored in SQL Server.

But that’s just the beginning. PolyBase becomes a data-rich foundation upon which to build powerful business applications. It dynamically creates columnar tables for your structured data, parallelizes the extraction of data from Hadoop and Azure—even pushing data to Hadoop clusters for additional processing.

Meanwhile, on the front end users can continue using their apps, consuming data and discovering new insights, all without needing to understand the finer points of data base management.

You can install PolyBase in one of two ways: using the SQL Server Installation Wizard or from the command-prompt window. See below for an example of the installation script.

Subsequently, you’ll also need to configure to PolyBase to connect either to Hadoop or Azure Blog Storage, using one of the following values:

  • 0 Disable Hadoop connectivity
  • 1 Hortonworks HDP 1.3 on Windows Server and blob storage
  • 2 Hortonworks HDP 1.3 on Linux
  • 3 Cloudera CDH 4.3 on Linux
  • 4 Hortonworks HDP 2.0 on Windows Server and blob storage
  • 5 Hortonworks HDP 2.0 on Linux
  • 6 Cloudera 5.1 on Linux
  • 7 Hortonworks 2.1 and 2.2 on Linux, Hortonworks 2.2 on Windows Server and blob storage

To achieve optimum app performance, even when dealing with larger datasets, consider creating a PolyBase scale-out group. PolyBase scale-out groups include one or more compute nodes, each of which includes a database engine and database movement service, as well as a head node that includes the SQL Server database engine, the PolyBase engine service and the PolyBase movement service. The following diagram gives you a better sense of how PolyBase scale-out groups can keep the data flowing.

CLICK HERE to read the full article and find out how SQL Server 2016 is creating new ways for you to visualize, analyze, and share your data!

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