BigDataNYC: A virtual data lake that avoids ‘hadooplification’

By September 10, 2015 May 12th, 2017 News

bigdatanyc: ROBIN Hyper-Converged Kubernetes Platform for Big Data and Databases: Consolidate, reduce costs, decouple compute, storage, get app & Data lifecycle management

Data is expensive to move and often CPU intensive. What if you could get four times the performance with a factor of four decrease in cost … and use your own file system? George Gilbert, host of theCUBE, from the SiliconANGLE Media team, sat down with Premal Buch, president and CEO of Robin Systems, and Rajeev Madhavan, Chairman of Robin Systems, during BigDataNYC 2015. Read more

 

A virtual data lake that avoids ‘hadooplification’ | #BigDataNYC

Premal Buch

Data is expensive to move and often CPU intensive. What if you could get four times the performance with a factor of four decrease in cost … and use your own file system? George Gilbert, host of  theCUBE, from the SiliconANGLE Media team, sat down with Premal Buch, president and CEO of Robin Systems, and Rajeev Madhavan, Chairman of Robin Systems, during BigDataNYC 2015.

Buch and Madhavan revealed what makes Robin Systems the next potential VMware, Inc.

Separating layers

Robin Systems has taken a unique approach in handling Big Data by separating data layers and using intelligent resource management combined with separating computing from data movement. By separating what was once a combined task, existing CPU resources can be spent on the application layer and not under the hood.

What makes it intelligent, though, is the way the Robin Systems has built its virtualized “data lake.”  This data lake can then be accessed by clusters and nodes and avoids problems like “hadooplification.”

Unique to the field

The company has done this by categorizing data into a hot layer that may run on faster systems, like a cache, and a cold layer that can sit on older, legacy-type storage solutions. Even more unique to this prioritization of data is the intelligent analytics that help to determine what belongs in what layer based on usage patterns.

Additionally, customers can create customized rules that direct data to an appropriate layer automatically. This leads to cost savings in virtually all areas of data management and avoids problems like hadooplification. The platform also isn’t bound to Hadoop; it can run any of the major file systems. And the benefits of utilizing Robin Systems’ platform are still apparent. It can simply best be summed up as a platform that’s “application agnostic,” according to Buch.

Watch the full video interview below, and be sure to check out more of SiliconANGLE and theCUBE’s coverage of BigDataNYC 2015.

Photo by SiliconANGLE

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