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| January 23, 2013 09:00 AM EST | Reads: |
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SAN FRANCISCO, CA -- (Marketwire) -- 01/23/13 -- Joyent, the high-performance cloud infrastructure company, today announced a new Apache Hadoop-based solution, built using the Hortonworks Data Platform (HDP), that allows companies to run enterprise-class Hadoop on the high-performance Joyent Cloud. Signifying Joyent's first entry into the big data landscape, this new Hadoop-based solution meets industry demand to reduce costs and dramatically decrease query response times. As measured by the software product development services company Altoros Systems, the following results were gleaned:
- Hadoop clusters on Joyent Cloud produced a nearly 3X faster disk I/O response time versus identically-sized infrastructure
- Or, the solution allows companies to cut their infrastructure costs by two-thirds with the same response time
Running Apache Hadoop on Joyent accelerates response times of distributed and parallel processing and improves the scaling of Hadoop clusters executing intensive data analytics applications. Through the use of its operating system virtualization and CPU bursting technology, Joyent is able to extract better response times and deliver results to data scientists and analysts faster.
"Joyent technology powers our service -- Instant Servers -- and is providing Telefonica Digital an advantage to deliver the fastest performing Hadoop big data solution in our marketplace," said Carlos Morales Paulin, Global Managing Director, M2M, Cloud Computing & Apps, Telefonica. "Joyent has inversed the big data cost equation while at the same time innovating how computing on large distributed and unstructured data can be accomplished for large enterprises. Our customers can now get insight from their data quicker than ever before without the massive cost that's typically associated with high-performance big data solutions."
Early users of the new solution are already reaping the advantages for massive, parallel and distributed workloads. By helping to address new interactive workloads not currently addressed in Hadoop, Joyent is dramatically reducing the time required for businesses to gain insight from their most vital data. Joyent's Hadoop solution will also offer a more consumer-friendly experience that can be added to existing Joyent Cloud implementations and easily configured to meet customer storage needs.
"Hortonworks Data Platform delivers the only complete 100 percent open source Apache Hadoop distribution, and is becoming the defacto standard for cloud offerings," said Mitch Ferguson, Vice President of Business Development, Hortonworks. "We are pleased to be working with Joyent in helping to create enterprise-class big data solutions for its customers."
"We are pioneering a new era of big data and our Hadoop offering is just the start of our 2013 agenda," said Jason Hoffman, CTO and Founder, Joyent. "We intend to continue bringing our technical expertise to the market and reverse the typical understanding of big data implementations -- that they're expensive and hard to use. We're committed to meeting the insatiable demand for faster analytics and data retrieval, changing how computing functions for the enterprise."
The Apache Hadoop solution is available for Joyent customers today. For more information, visit: Joyent.com/hadoop.
About Joyent:
Joyent is the high-performance cloud infrastructure company offering enterprises and developers the best public, and hybrid cloud infrastructure for today's demanding real-time web and mobile applications. Joyent delivers public and hybrid cloud services to some of the most innovative companies in the world, including, LinkedIn, Major League Baseball, Modcloth and Voxer. Node.js, the open source server-side JavaScript project developed and sponsored by Joyent, provides developers and enterprises such as Microsoft, Wal-Mart and Comcast Labs with the most powerful runtime for developing data-intensive, real-time apps. For more information visit http://www.joyent.com.
Kate Reed
joyent@launchsquad.com
(415) 625-8555
Published January 23, 2013 Reads 404
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