High-performance computing leader Platform Computing hopes to capitalize on the big data movement by spreading its wings beyond its flagship business of managing clusters and grids and into managing MapReduce environments, as well. As was the case when Platform made its foray into cloud computing in 2009, the news is significant because Platform has a solid foundation among leading businesses, especially in the financial services industry. If large financial organizations were leery about taking their analytics efforts to the next level, Platform might help spur them along, and it might help drive even further choice for customers by driving other HPC vendors into the MapReduce and Hadoop space.

Technologically, Platform’s new product, called MapReduce Workload Manager, extends the management capabilities of the company’s flagship LSF and Symphony products to MapReduce systems. The product is unique because it doesn’t tie users to any specific MapReduce implementation or file system, rather letting them mix and match their processing and storage software. It works with Apache’s Hadoop MapReduce and Hadoop Distributed File System (HDFS), but also with Apache Hive and Apache Pig — all of which use Java APIs — but also with IBM InfoSphere BigInsights, and Python and C++ MapReduce APIs.

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