MapR Adds Integrated Search to its Hadoop Platform and Launches M7 with Built-In NoSQL Solution

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MapR Technologies is integrating LucidWorks Search with the MapR Platform for Apache Hadoop to enable customers to perform predictive analytics, full search and discovery; and conduct advanced database operations on one platform. Integrated search and discovery on the MapR Big Data platform is currently in beta, and will be generally available next quarter in MapR's just-released M7 Edition, which combines Hadoop with NoSQL capabilities.

According to the company, the new MapR search capability works directly on Hadoop data but can also index and search standard files without having to perform any conversion or transformation. All search content and results are protected with enterprise-grade high availability and data protection, including snapshots and mirrors, enabling a full restore of search capabilities. By integrating LucidWorks’ search technology, MapR and its customers benefit from the added value that LucidWorks Search delivers in the areas of security, connectivity and user management for Apache Lucene/Solr that users would otherwise have to develop from scratch using Solr alone.  The LucidWorks/MapR product integration and bundling extends the two companies’ relationship. In 2011, they formed a joint marketing agreement. In February, they deepened their relationship, releasing a connector between the companies’ two products.

The new M7 Edition provides scale, consistency, reliability and continuous low latency, which MapR says removes the trade-offs that organizations often must deal with when deploying a NoSQL solution.

The MapR M7 Edition is designed to deliver reliability and performance without requiring compactions or background consistency checks to work smoothly.  M7 delivers over one million operations/sec with a 10-node cluster and provides scalability advantages with support for up to one trillion tables across thousands of nodes. In addition, says MapR, M7 provides instant recovery from failures, ensuring high availability (99.99%) for HBase and Hadoop applications.

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