Elasticsearch Enhances Big Data Analytics Tools for Hadoop 2.0

Elasticsearch has broadened its Big Data analytics profile with the release of a new connector for Hadoop 2.0, as well as certification on Cloudera Enterprise 5.

The certification makes Elasticsearch, which was founded in 2012 and which already supported the HortonWorks and MapR Big Data platforms, officially compatible with all of the major Hadoop distributions.

Meanwhile, the updated version of the Elasticsearch connector for Hadoop allows the company's data analytics tools to interact with information stored in the most recent versions of Apache Hadoop. The connector also provides a snapshot feature that "makes it easy to take a snapshot of data within Elasticsearch—perhaps a year’s worth—and archive it in Hadoop," according to the company. Snapshots later can be restored back into Elasticsearch for further analysis.

Elasticsearch aims to add value to Big Data storage by helping enterprises to take advantage of the massive storage capaibilities that Hadoop provides while performing rigorous analysis of that data with much greater speed than Hadoop alone allows. The company reports that its data analytics platform is already in use by a number of major organizations, including Bloomberg, Comcast, eBay, Facebook, GitHub, Mayo Clinic, McGraw-Hill, Netflix, The New York Times, Target, Verizon, WordPress and Yelp.

"Hadoop was created to store and archive data at a massive scale, but businesses need to be able to ask, iterate and extract immediate insights from this data—which is what we designed our products for," said Steven Schuurman, Elasticsearch cofounder and CEO. "With today’s certification from Cloudera, Elasticsearch now works with all Apache-based Hadoop distributions, and with it, solves the last mile of big data Hadoop deployments by getting big insights, fast."