Red Hat and Hortonworks blend Hadoop into enterprise infrastructure for big data projects

Red Hat and Hadoop specialist Hortonworks have announced a partnership aimed at making big data projects easier to operate by integrating the Hortonworks Data Platform (HDP) with key Red Hat infrastructure products, including Red Hat Linux with OpenJDK and its Red Hat Storage Server.

The partnership represents a strategic alliance that will see joint customer support from the two firms, Red Hat and Hadoop said.

First fruits of the partnership are the Hortonworks Data Platform (HDP) on Red Hat Storage, HDP on Red Hat Enterprise Linux with OpenJDK, and Red Hat JBoss Data Virtualization with HDP. The first is currently a beta, while the other two are available now.

Ranga Rangachari, Red Hat vice president for Storage and Big Data, said that the partnership had worked hard at combining the two firms’ respective product stacks, and enabling customers to inject Hadoop workloads into the resulting stack.

Shaun Connolly, vice president of corporate strategy at Hortonworks, flagged up the HDP integration with Red Hat Storage Server as of key importance in particular, as this enables analytics to be carried out in place in the data where it resides.

Meanwhile, integration with Red Hat JBoss Data Virtualisation provides a single common data model for developers and data analysts, according to the two firms.

“This enables you to pull data from multiple data sources including NoSQL, enterprise applications, and now Hadoop. It normalises the data model and makes it easier for developers to write apps,” said Connolly.

“People want to consume data in Hadoop using their existing skills and tools when building new analytic apps. This integration speaks to enabling business analysts and application developers in the enterprise today,” he added.

However, another key area is enabling simple deployment of Hadoop into OpenStack cloud environments via HDP on Red Hat Enterprise Linux with OpenJDK.

Rangachari said that this would enable organisations to easily deploy Hadoop workloads on premise or in the public cloud, or both.

“Hadoop lends itself well to this, as it can scale out easily. You can extend out to the public cloud if necessary, and bring it all back on-premise at a later date if necessary,” he said.

“Now we truly have a best-of-breed solution that is truly open as well as giving customers choice,” he added.

The two firms are also working with OpenStack on the Savanna project, which aims to deliver a simple, standardised way to provision a Hadoop cluster on top of OpenStack, Rangachari said.