Revolution Analytics has integrated Revolution R Enterprise with Hortonworks Data Platform. In a move designed to help Hadoop customers derive more value from their big data technology investments, Revolution Analytics and Hortonworks are co-developing “in-Hadoop predictive analytics” without the need to import or export data from Hadoop, David Smith, vice president of marketing and community at Revolution Analytics, tells 5 Minute Briefing.
The initiative will enable Revolution R Enterprise and Hortonworks Data Platform customers to use the big data analytics capabilities of Revolution R Enterprise ScaleR on a server streaming data directly from HDFS or by importing data from HBase, and write their own data distillation algorithms in the R language using the MapReduce paradigm of Hadoop.
Revolution Analytics has already invested its support for the Hadoop ecosystem, and this new Hortonworks partnership follows other integrations that Revolution Analytics has forged with other companies with Hadoop-based software, including Cloudera CDH3 and CDH4, and IBM BigInsights version 2.
According to the vendor, while Hadoop has become a leading option for storing and performing operations on big data, R has emerged as “the tool of choice” for data scientists modeling and running advanced analytics. Revolution Analytics provides customers with a validated and certified stack of Hadoop (including from validated hardware partners with reference architectures), and Revolution R with RHadoop.
Revolution Analytics has developed “ConnectR for Hadoop,” which provides open source R packages and proprietary technologies that bring advanced R analytics to Hadoop distributions. ConnectR for Hadoop allows developers to manipulate Hadoop data stores directly from HDFS and HBASE—and gives R programmers the ability to write MapReduce jobs in R using Hadoop Streaming. ConnectR for Hadoop is included with Revolution R Enterprise 6 Server for Linux, and includes support for the Revolution Analytics sponsored open source project RHadoop.
For more information, go to the Revolution Analytics website.