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April 24, 2014

Elasticsearch's Analytics Capability Integrated with MapR Distribution for Apache Hadoop

The MapR Distribution for Apache Hadoop is now available with Elasticsearch’s real-time search and analytics capability, using which one can easily search and store huge amount of data in real-time.

Elasticsearch is a powerful open source search and analytics engine that allows users to seamlessly extend their capabilities beyond simple full-text search and realize real-time search results from an index of over 10 billion documents.

Built from the ground up and ideal for business-critical production applications, MapR is termed as a complete distribution for Apache Hadoop that packages more than a dozen projects from the Hadoop ecosystem to provide a broad set of Big Data capabilities. It also consists of a range of enterprise-grade features like high availability, provision for data protection and disaster recovery, multi-tenancy, volume support, and more.

Now with the combined prowess of MapR and Elasticsearch, one can easily deploy a scalable, distributed architecture that is capable of offering quicker search and discovery performance across tremendous amounts of information. Customers are sure to receive production-ready technologies that enable real-time access for querying and examining the big data stored in Hadoop.

Shay Banon, founder and chief technology officer at ElasticSearch, stated, “Starting with the Elasticsearch-Hadoop project announced six months ago and underscored by this partnership with MapR, we are helping Hadoop users enhance their workflows with a full-blown search engine that scales no matter the amount of data. With Elasticsearch, developers and data-hungry businesses now have a way to ask better questions of their data and get clearer answers, significantly faster, in return.”

MapR is also said to be the first Hadoop distribution to integrate?enterprise-grade search allowing customers to execute predictive analytics, full search and discovery and conduct advanced database operations. These features combined with Elasticsearch’s real-time analytics, logging and search features should result in numerous possibilities for those working with vast amounts of data. 




Edited by Maurice Nagle
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