This is the first product related to big data from Joyent, built using the Hortonworks Data Platform (HDP). Using operating system virtualization and CPU bursting technology, the company claims to achieve better response time. It also says that 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.
Let us look at some of the key features of the hadoop solution. Tuning of the big data servers to reduce sort and query latency that helps end-users arrive at answers faster is responsible for faster response times. HDP provides the tools to install, configure and provision your Hadoop deployments on Joyent cloud. Robust security is provided by two layers of protection, a zone within a container. Big data analytical processes can be securely run in the cloud. Joyent enables you to maintain the operational flexibility and control (scale up, scale down, re-size machines) to multiple Hadoop clusters.
The key in dramatically reducing the time required for businesses to gain insight from their most vital data seems to be addressing new interactive workloads that is not currently addressed in Hadoop. It seems early users of the new solution are already reaping the advantages for massive, parallel and distributed workloads, as it evident from the quotes of their executives in the press release.
Last year Joyent has received a funding of $85 million for its global expansion and innovation as reported by us.
According to Altoros Systems, a software product development services company, hadoop clusters on Joyent cloud produced a nearly 3X faster disk I/O response time versus identically-sized infrastructure. This allows companies to cut their infrastructure costs by two-thirds with the same response time.
“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.”
[Image Credits: Joyent]