Newsletters




New Revolution R Enterprise Boosts Big Data Analytics Capabilities


Bookmark and Share

Revolution Analytics, a commercial provider of software, services and support for the open source R project, has announced the general availability of Revolution R Enterprise 6.0, the latest release of its commercial-grade analytics software for R-based data analytics.The company’s flagship Revolution R Enterprise product is designed to meet the production needs of large organizations in industries such as finance, life sciences, retail, manufacturing and media. According to the company, the new iteration of Revolution R Enterprise delivers better performance, productivity, and enterprise-readiness for statistical analysis of very large data sets, helping to provide Rdevelopers with the tools required to meet the growing demands and requirements of data-driven businesses.

According to David Smith, vice president of marketing and community at Revolution Analytics, the company’s mission is to bring the open source R analytics software to the commercial market. It does this by enhancing it to work with big data by making it more powerful in terms of performance and scalability, making people more productive with its integrated development environment, and generally enabling enterprise readiness for companies that want to adopt the R language for their data analysis needs. “We are not a data company; we are not a database company.  We do analytics software but our software works with data coming out of various data platforms, including logical databases, Hadoop, data appliances like IBM Netezza, and flat files for doing data analysis, which can then be delivered up  into reporting and business intelligence systems,” he notes. In addition, using the built-in RevoScaleR package in Revolution R Enterprise, R users can process, visualize and model terabyte-class data sets quickly without requiring expensive or specialized hardware. 

The main theme of the new release was to expand out the data platforms upon which users can do big data predictive modeling, Smith says. According to Revolution Analytics, key highlights of Revolution R Enterprise 6.0 include:

  • Platform LSF Cluster Support—Now supports distributed computing on multi-node Platform LSF grids. Support on Windows-based grids provided via Microsoft HPC Server.
  • Cloud-based Analytics with Azure Burst—Switch computations from a local Microsoft Windows HPC Server cluster to the Azure Cloud with a single command.
  • Big-Data Generalized Linear Models—Support big-data predictive models used in insurance, finance and biotech industries. Use a multi-node server or distributed grid for fast analytics on big data.
  • Direct Analysis of SAS, SPSS, ASCII and ODBC dataAnalyze proprietary data formats without the need for SAS/SPSS licenses.
  • Updated R 2.14.2 engine—Improves performance, parallel programming capabilities. In addition, Revolution Analytics’ open-source RHadoop project (for Hadoop integration) is updated to work with this new engine.

More information is available from the Revolution Analytics website. 


Sponsors