This post originally appeared at http://hortonworks.com/blog/red-hat-hortonworks-make-big-data-easily-consumable
Red Hat and Hortonworks are collaborating to bring enterprise ApacheTM Hadoop® to the open hybrid cloud. Ok, great, you say, but isn’t that old news dating back to the beginning of this year?
Well, yes it is, but some gifts just keep on giving. Back in February 2014, Red Hat and Hortonworks announced that they would be working together to integrate the Hortonworks Data Platform (HDP) with a number of Red Hat technologies, including Red Hat Enterprise Linux, Red Hat Enterprise Linux OpenStack Platform, OpenShift Enterprise, Red Hat Storage Server, Red Hat JBoss Middleware, as well as collaborate on contributions to open source community projects such as Apache Ambari, and OpenStack Savanna. Since then we’ve been busy building out the integration components necessary for the technologies to work easily together. We’ve also documented the use cases that assist customers with the knowledge to use the technologies together effectively. And lastly, we’ve readied our support teams to collaboratively support our customers deploying the joint technologies and use cases.
A question that gets asked about the Red Hat and Hortonworks relationship is why it is necessary to involve all of these technologies instead of having the touch points between them be much simpler and fewer in number?
Well, the relationship extends to many parts of today’s modern technology stack because that’s how much big data use cases have become instrumental to the lifeblood of many enterprises’ operations. In the past, big data was mostly about Hadoop and batch-only MapReduce operations. Today, big data stakeholders throughout many enterprises, including data architects, operators, and application developers, have come to rely on enterprise Hadoop. The Hadoop capabilities include multiple ways of interacting with data, including interactive SQL, in-memory analytics and real-time stream processing – all while interacting with consistent security and governance. As a result, an enterprise Hadoop platform should be able to interact both with the resources provided in the infrastructure layer and the services provided at the application layer. At the infrastructure layer, it’s only natural that HDP should perform well with Red Hat Storage, Red Hat Enterprise Linux and Red Hat Enterprise Linux OpenStack Platform. At the application layer, because of the expanded number of big data use cases, HDP can integrate with JBoss Data Virtualization, JBoss Data Grid, and JBoss BRMS.
With the explosive growth of big data applications, what does a modern data architecture look like? Well, we know that even with an enterprise Hadoop platform, an organization will still have diverse and distributed data sources that fall outside the scope of the "data lake", an enterprise-wide repository for the volumes of unstructured and semi-structured data that today’s businesses are amassing. Big data stakeholders can now take advantage of the efficiency, opportunities and insights that come from managing and analyzing their data by combining data virtualization with the data lake.
Through the Red Hat and Hortonworks alliance, JBoss Data Virtualization has been integrated with HDP. JBoss Data Virtualization facilitates and improves the use of HDP in the enterprise by integrating HDP with existing enterprise data sources, adding the ability to query HDP data in real-time and adding security and governance to the big data infrastructure.
For more information about how all this comes together to enable an open hybrid cloud, stay tuned to Red Hat and Hortonworks’ developments for HDP on OpenStack, HDP and JBoss Data Virtualization on Red Hat OpenShift, HDP and Red Hat Enterprise Linux, HDP and Red Hat Enterprise Linux OpenStack Platform, and HDP and Red Hat Storage.
How can you learn more about the integration of HDP with Red Hat JBoss Middleware technologies, such as JBoss Data Virtualization?
Sign up for our upcoming webinar series starting September 3, with follow up deep dive demonstration sessions on September 10 and September 17. These webinars will be available on-demand following the live presentations.