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Joyent has rolled out a new service that offers enterprises the ability to analyse big data using Hadoop.
The Hadoop service uses Hortonworks Data Platform running on Joyent’s high-performance cloud infrastructure. The firm joins ranks with AWS, GoGrid, IBM and Microsoft in offering a cloud-based big data service to customers.
Joyent claims its Hadoop offering - which is available immediately - runs three times faster than its rivals and will allow enterprises to process high-performance data applications at a third of the cost of other cloud offerings.
It said that running Apache Hadoop on Joyent accelerated response times of distributed and parallel processing and improved the scaling of Hadoop clusters executing intensive data analytics applications. It added that through the use of its operating system virtualisation and CPU bursting technology, it was able to “extract better response times and deliver results to data scientists and analysts faster.”
“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 of 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.”
Communications giant Telefonica is an early adopter of Joyent’s Hadoop service.
“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, the firm's global managing director of M2M, cloud computing and apps.
“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."