Boston, MA 10/16/2014 (wallstreetpr) – EMC Corporation (NYSE:EMC) and Pivotal disclosed the unveiling of the Data Lake Hadoop Bundle 2.0 providing a total turn-key offering featuring analytics, storage and computing for their customers. It would help them establish scale-out Data Lakes for analytics of predictive.
According to a statement from EMC Corporation (NYSE:EMC), Data Lakes were gaining momentum due to an infinitely scalable storehouse for key data generated by next-generation, as well as, traditional workloads. It said that the scale-out Dale Lake has been designed to be ready for the enterprise to support organizations realize immediate value of their business from Big Data.
EMC said that the product would continue to maintain lower costs through acquisition and management compared to assembled disparate parts. The Data Lake Hadoop Bundle 2.0 was meant to support organizations keen to fasten the value of Bid Data objectives in the enterprise sector. The solution consisted of the analytical system of high performance; pre-tested featuring EMC Corporation (NYSE:EMC)’s advanced analytics and storage on Hadoop with enterprise appliances. It would power a single, easy and focused to implement the solution.
EMC Corporation (NYSE:EMC) said that Data Lake Hadoop Bundle.2.0 was available generally. HDFS-ready, scale-out, enterprise-class Isilon NAS storage nodes were also included in Data Lake Hadoop Bundle 2.0. For advanced analytics of best-in-class on Hadoop, Pivotal HAWQ pre-configured and tough Lake Hadoop Bundle 2.0 was also included.
EMC’s President for products and manufacturing, Jeremy Burton, said that Big Data was some organizations’ top mind throughout the world. However, EMC Corporation (NYSE:EMC) said that for many, it meant that they were concerned on how to harness its value and store. He said that the bundled offers from superior system of performance for leveraging Hadoop for analytics of big data. It was truly a case of turnkey with an end-to-end solution meant to command big data amounts successfully.