– Kumar Sreekanti, CEO of BlueData, says:
BlueData, the pioneer in private clouds, today launched EPICTM Enterprise, the industry’s first Big Data software to enable enterprises to create a self-service cloud experience on premise. The EPIC platform is powered by BlueData’s patent-pending technology, including DataTapTM and IOBoostTM, which eliminates time-consuming data movement and unnecessary data duplication without compromising performance. With the release of EPIC, BlueData is democratizing big data by streamlining and simplifying big data infrastructure and eliminating complexity as a barrier to adoption. Enterprises of all sizes can now build agile, secure and cost-effective Big Data deployments that deliver value in days instead of months and at a cost savings of 50%-75% compared with traditional approaches. By making Big Data accessible to all, enterprises can get the same value out of their on-premise Big Data as companies like Google, Facebook and Yahoo at a fraction of the cost, and with far fewer resources.
BlueData is also announcing the availability of EPIC One, a full-featured community edition, which allows users to experience the power of multi-app, multi-version instant clusters on a single physical node.
With this announcement, BlueData is making Big Data accessible to companies of all sizes, allowing them to create flexible and scalable on-premise production and test environments where people can work with, and experiment with, a variety of Big Data applications. With the BlueData EPIC software platform, organizations can create flexible and scalable on-premise production and test environments where people can work with a variety of big data applications and iterate quickly with full control.
Blue Data also announced that it has joined the Hortonworks Technology Partner program, receiving Hortonworks Certification for BlueData’s EPIC platform. Hortonworks is the leading contributor to and provider of Apache™ Hadoop®. BlueData EPIC with Hortonworks Data Platform (HDP) empowers IT architects and data scientists to create instant, individualized virtual clusters for each of their Big Data users in minutes—all while keeping the data in its original location.
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