“Big Data” seems to be on the tip of everyone’s tongue in recent months, and here at the Platform this has been no exception. Applying MapReduce applications to the data deluge has so much potential, but in Derrick Harris’ sage words “Hadoop may be hot, but it needs to be useful” (source: GigaOM). With this in mind, Platform has set itself to applying its 18-year experience in policy-driven workload scheduling to the development of a MapReduce solution ready for the enterprise and to tackle its unique challenges. Back in March, Platform strongly hinted at a forthcoming product, but now it’s official.
Platform announced the launch of Platform MapReduce, the industry’s first enterprise-class, distributed runtime engine for MapReduce applications, with general availability to come at the end of July. The new solution will be able to manage MapReduce applications in a cluster (even multiple applications on a shared cluster) across an entire distributed file system. With more than 10,000 policy levels and support for up to 300,000 concurrent tasks, Platform MapReduce provides unparalleled manageability and scale, while ensuring high resource utilization to maximize ROI. Applicable to industries across multiple sectors, these key features can enable such diverse functions as compliance and regulatory reporting for financial services and government agencies; customer churn prevention for telecommunications; and genome sequencing analysis for life sciences.
Platform MapReduce also supports open distributed file system architecture, including immediate support for Hadoop Distributed File System (HDFS) and Appistry Cloud IQ – with more to come! To ensure that open source solutions, in this case those used with the Platform MapReduce distributed runtime engine, receive the world-class support enterprise customers demand, Platform has also signed the Apache Corporate Contributor License Agreement to contribute to the development of Apache-based, open-source Hadoop Distributed File System (HDFS).
With Platform MapReduce and world-class support, the enterprise is now ready to tackle the data deluge!
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