Intel Distribution for Apache Hadoop software built from the silicon up
New software offering now available and supported by more than 20 partners
TO ensure more organizations and people have the ability to make use of the vast amounts of data that are generated, collected and stored everyday, or big data, Intel has announced the availability of the Intel Distribution for Apache Hadoop software.
The software offering is built from the ‘silicon up’ to deliver industry-leading performance and security, the company said in a statement.
The ability to analyze and make sense of big data has the profound potential to transform human society by enabling new scientific discoveries, business models and consumer experiences, Intel said.
Yet, only a small fraction of the world is able to extract meaning from all of this information because the technologies, techniques and skills available today are either too rigid for the data types or too expensive to deploy.
Hadoop is an open source framework for storing and processing large volumes of diverse data on a scalable cluster of servers that has emerged as the preferred platform for managing that data.
With even more information coming from billions of sensors and intelligent systems also on the horizon, the framework must remain open and scalable as well as deliver on the demanding requirements of enterprise-grade performance, security and manageability, Intel said.
“People and machines are producing valuable information that could enrich our lives in so many ways, from pinpoint accuracy in predicting severe weather to developing customized treatments for terminal diseases,” said Boyd Davis, vice president and general manager of Intel’s Datacenter Software Division.
“Intel is committed to contributing to and supporting the open source community to provide the industry with a better foundation from which it can push the limits of innovation and realize the transformational opportunity of big data.”
Intel said it is delivering an innovative open platform built on Apache Hadoop that can keep pace with the rapid evolution of big data analytics. It claimed the Intel Distribution is the first to provide full encryption with support of Intel AES New Instructions (Intel AES-NI) in the Intel Xeon processor.
By incorporating silicon-based encryption support of the Hadoop Distributed File System, organizations can now securely analyze their data sets without compromising performance.
The optimizations made for the networking and IO technologies in the Intel Xeon processor platform also enable new levels of analytic performance, the company said.
Analyzing one terabyte of data, which would previously take more than four hours to fully process, can now be done in seven minutes thanks to the data-crunching combination of Intel’s hardware and the Intel Distribution.
Considering the world generates one thousand terabytes of data every 30 seconds or the equivalent of 13 years of HD video, the power of Intel technology opens up the world to even greater possibilities, Intel said.
The addition of the Intel Manager for Apache Hadoop also simplifies the deployment, configuration and monitoring of the cluster for system administrators as they look to deploy new applications, the company added.
Using the Intel Active Tuner for Hadoop Software optimal performance is automatically configured to take the guesswork out of performance-tuning. Until now, this required a specialized understanding of each application’s use of system resources along with the Hadoop configuration and performance benchmarks.
Intel said it is working with strategic partners to integrate this software into a number of next-generation platforms and solutions, and to enable deployment in public and private cloud environments.
The Intel Distribution is available in the United States and China and is supported by Amax, Amazon, Cisco, Colfax, Datameer, Dell, EnPointe, Informatica, Infosys, Kitenga, LucidWorks, MarkLogic, Pentaho, Persistent, Red Hat, Revolution Analytics, SAP, SAS, Savvis, Silicon Mechanics, SoftNet, SuperMicro and TeraData.
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