A free developer edition of Microsoft R Server, formerly Revolution R Enterprise, has been announced.
Microsoft acquired the R language technology early in 2015 when it took over Revolution Analytics, and has now announced a range of products based on the statistical analysis language.
There have been a number of updates to the Revolution R products, and R has been integrated with SQL Server, PowerBI, Azure and Cortana Analytics.
The products have been renamed, so that Revolution R Enterprise is now Microsoft R Server, and is available in a commercial version or for download free of charge for developers and students.
The developer version can be used for the testing, development and creation of R scripts and models.It will be available via Visual Studio Dev Essentials, and you'll need a Microsoft account to sign up for it.
Microsoft's Data Science Virtual Machine will also come with a preinstalled and preconfigured version of the developer version. The Data Science VM is described as "a Windows Server 2012-based custom virtual machine image on the Azure marketplace containing several popular tools that can be used by data scientists and developers for advanced analytics."
Microsoft R Server 2016 is the version designed for use on servers, Hadoop clusters, and data warehouses, and in addition to its new name it includes an updated R engine (R 3.2.2), new fuzzy matching algorithms, and the ability to write to databases via ODBC.
Joseph Sirosh, Corporate Vice President of Microsoft Data Group said in a post on the Machine Learning blog that:
"Delivering Microsoft R Server across multiple platforms allows our enterprise customers to standardize advanced analytics on one core tool, regardless of whether they are using Hadoop (Hortonworks, Cloudera and MapR), Linux (Red Hat and SUSE) or Teradata. For Windows, Microsoft R Server will be included in SQL Server 2016 as SQL Server R Services."
Sirosh said R Server supports the full range of analytics - exploration, analysis, visualization and modeling, and is fully compatible with R scripts, functions and CRAN packages.
He said the new version also addresses the in-memory limitations of open source R by adding parallel and chunked processing of data in Microsoft R Server, enabling users to run analytics on data much bigger than what fits in main memory. The new release improves performance by using multi-threaded processor optimized computations provided by Intel Math Kernel Libraries (MKL). The management of R package versions has also been simplified.
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