{"id":13781,"date":"2015-10-28T07:45:00","date_gmt":"2015-10-28T14:45:00","guid":{"rendered":"https:\/\/blogs.technet.microsoft.com\/dataplatforminsider\/2015\/10\/28\/sql-server-2016-community-technology-preview-3-0-is-available\/"},"modified":"2024-01-22T22:50:15","modified_gmt":"2024-01-23T06:50:15","slug":"sql-server-2016-community-technology-preview-3-0-is-available","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/en-us\/sql-server\/blog\/2015\/10\/28\/sql-server-2016-community-technology-preview-3-0-is-available\/","title":{"rendered":"SQL Server 2016 Community Technology Preview 3.0 is available"},"content":{"rendered":"

The SQL Server engineering team is pleased to announce the availability of SQL Server 2016 October public preview release CTP 3.0.\u00a0 This release is a key milestone for SQL Server 2016 with all the key capabilities landing, including RRE integration. To learn more about this release, visit the SQL Server 2016 preview page<\/a>.<\/p>\n

To experience the new, exciting features in SQL Server 2016 and the new rapid release model, download the preview<\/a><\/strong>, and start evaluating the impact these new innovations can have for your business. Have questions? Join the discussion of the new SQL Server 2016 capabilities at MSDN<\/a> and Stack Overflow<\/a>. If you run into an issue or would like to make a suggestion, you can let us know using Microsoft\u2019s Connect tool<\/a>. We look forward to hearing from you.<\/p>\n

Advanced Analytics (RRE integration)<\/h1>\n

With this release, we are very excited to announce the public availability SQL Server R Services in SQL Server 2016, an Advanced Analytics capability which supports enterprise-scale data science, significantly reducing the friction for adopting machine learning in your business. SQL Server R Services is all about helping customers embrace the highly popular open source R language in their business. R is the most popular programming language for Advanced Analytics. You can use it to analyze data, uncover patterns and trends and build predictive models. It offers an incredibly rich set of packages and a vibrant and fast-growing developer community. At the same time, embracing R in an enterprise setting presents certain challenges, especially as the volume of data rises and with the switch from modeling to production environments. Microsoft SQL Server R Services with in-database analytics helps customers embrace this technology by supporting several scenarios. Two of the key scenarios are:<\/p>\n

One<\/strong>: Data Exploration and Predictive Modeling with R over SQL Server data<\/p>\n

The data scientist can choose to analyze the data in-database or to pull data from SQL Server and analyze it on the client machine (or a separate server). Analyzing data in-database has the advantage of performance and speed by removing the need to move data around and leverage the strong compute resources on the SQL Server. RevoScaleR package and APIs contains a set of common functions and algorithms that were designed for performance and scale, overcoming R limitations of single-threaded execution and memory bound datasets.<\/p>\n

Two<\/strong>: Operationalizing your R code using T-SQL<\/p>\n

For SQL Server 2016 CTP3, we support ad-hoc execution of R scripts via a new system stored procedure. This stored procedure will support pushing data from a single SELECT statement and multiple input parameters to the R side and return a single data frame as output from the R side.<\/p>\n

execute<\/span> sp_execute_external_script.<\/span><\/p>\n

\"<\/a><\/p>\n

Transactional replicate from SQL Server to Azure SQL DB<\/strong> in new in CTP3. Now you can setup Azure SQL DB as a subscriber of transaction replication, allowing you to migrate data from SQL Server instance on-premises or in IaaS to Azure SQL database without downtime. The replication is one way in this release, and works with SQL Server 2016, SQL Server 2014 and SQL Server 2012. This is the same Transactional Replication technology you have been using for many years on premise. As you configure a subscriber (from SSMS or by script), instead of entering an instance name, you enter the name of your Azure SQL DB subscription along with the associated login and password. A snapshot (as in a Replication Snapshot) will used to initialize the subscription and subsequent data changes will be replicated to you Azure SQL DB in the same transactional consistent way you are used to. A transactional publication can deliver changes to subscribers both in Azure SQL DB and\/or on premise\/Azure VM. There is no Replication service hosted in Azure for this. Everything is driven from on-premise distribution agents. To use this feature, you just need to set it up the way you do to replicate on-premises: Install the Replication components, configure the Distributor, the Publisher and create the Publication, the Articles and you the Subscriptions. In this case, one of the subscriptions will be your Azure SQL DB.<\/p>\n

In-Memory<\/strong> improvements in this release:<\/p>\n