January 30, 2013
PALO ALTO, Calif., Jan. 30 – Hortonworks, a leading contributor to Apache Hadoop, today announced that the Hortonworks Data Platform (HDP), the industry’s only enterprise-ready, 100-percent open source platform powered by Apache Hadoop, has achieved certification for Rackspace Private Cloud. As a part of The Rackspace Open Cloud platform, the company launched the Rackspace Private Cloud Software in August 2012, with thousands of organizations in over 125 countries spanning all continents downloading the product. HDP is the only Apache Hadoop distribution to have received this certification. Combining the power of enterprise-class Apache Hadoop in HDP with Rackspace Private Cloud, organizations now have a secure, scalable environment to refine, explore and enrich their data using Hadoop.
With HDP, data can be processed from applications that are hosted on Rackspace Private Cloud environments, allowing organizations to quickly and easily obtain additional business insights from this information. The provisioning, monitoring and management components of HDP are important enablers for the integration with the Rackspace Private Cloud, providing an easy path for getting data into and out of the cloud.
“The Hortonworks Data Platform powered by Apache Hadoop assessed and certified for Rackspace Private Cloud, enables enterprise organizations to test the open source big data platform’s compatibility with OpenStack-powered private clouds,” said Paul Rad, vice president, Private Cloud, Rackspace. “As a consistent, supportable and proven platform, Rackspace Private Cloud is now enabling Hortonworks Data Platform customers to quickly and easily access and analyze data from across their private cloud-powered deployments in Apache Hadoop.”
After a detailed testing and validation process, Hortonworks Data Platform is now certified for building private clouds based on Rackspace Private Cloud Software v2.0. HDP qualifies for the Rackspace Private Cloud Open Reference Architecture “Mass Compute with External Storage”, signifying that it has met specific integration and interoperability standards and works effectively with Rackspace Private Cloud Software.
“The Hortonworks Data Platform is emerging as the de facto Apache Hadoop distribution for cloud providers, and the certification for Rackspace Private Cloud is another significant step in the enterprise viability of Hadoop,” said Herb Cunitz, president, Hortonworks. “Our commitment to the 100-percent open source model ensures that cloud providers will avoid any vendor lock-in when deploying HDP and Rackspace Private Cloud, and further extends the Apache Hadoop ecosystem to the private cloud, providing another method for exploring and enriching enterprise data with Hadoop.”
Hortonworks is a leading commercial vendor of Apache Hadoop, the preeminent open source platform for storing, managing and analyzing big data. Our distribution, Hortonworks Data Platform powered by Apache Hadoop, provides an open and stable foundation for enterprises and a growing ecosystem to build and deploy big data solutions. Hortonworks is the trusted source for information on Hadoop, and together with the Apache community, Hortonworks is making Hadoop more robust and easier to install, manage and use. Hortonworks provides unmatched technical support, training and certification programs for enterprises, systems integrators and technology vendors.
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
Frank Ding, engineering analysis & technical computing manager at Simpson Strong-Tie, discussed the advantages of utilizing the cloud for occasional scientific computing, identified the obstacles to doing so, and proposed workarounds to some of those obstacles.
The private industry least likely to adopt public cloud services for data storage are financial institutions. Holding the most sensitive and heavily-regulated of data types, personal financial information, banks and similar institutions are mostly moving towards private cloud services – and doing so at great cost.
May 16, 2013 |
When it comes to cloud, long distances mean unacceptably high latencies. Researchers from the University of Bonn in Germany examined those latency issues of doing CFD modeling in the cloud by utilizing a common CFD and its utilization in HPC instance types including both CPU and GPU cores of Amazon EC2.
May 10, 2013 |
Australian visual effects company, Animal Logic, is considering a move to the public cloud.
May 10, 2013 |
Program provides cash awards up to $10,000 for the best open-source end-user applications deployed on 100G network.
May 08, 2013 |
For engineers looking to leverage high-performance computing, the accessibility of a cloud-based approach is a powerful draw, but there are costs that may not be readily apparent.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/02/2012 | AMD | Developers today are just beginning to explore the potential of heterogeneous computing, but the potential for this new paradigm is huge. This brief article reviews how the technology might impact a range of application development areas, including client experiences and cloud-based data management. As platforms like OpenCL continue to evolve, the benefits of heterogeneous computing will become even more accessible. Use this quick article to jump-start your own thinking on heterogeneous computing.