LucidWorks Big Data now Integrated with MapR

By on February 22, 2013

See this new research note from Ventana Research discussing how LucidWorks Big Data connects with and integrates Mapr. The author, Mark Smith, discusses how LucidWorks Big Data integrates both MapR and key Apache Open Source technologies to produce a developer-friendly Big Data application platform.

The research note examines how search is the UI for Enterprises to access all of their Big Data, but inadequate search capabilities within Big Data have diminished companies abilities to enable data-driven decisions.

LucidWorks Big Data consists of a single, integrated framework that takes advantage of key Apache technologies. The implementation consists of Open Source projects such as HBase for storage and access, Kafka for distributed publish and subscribe, Mahout for scalable machine learning, Pig for Map-Reduce scripting and ZooKeeper for distributed coordination. Traditional integration and implementation of all of these elements typically results in a many-month’s long effort. LucidWorks Big Data’s pre-install integration and certification allows for exceptionally quick implementation of Big Data solutions with greatly reduced testing and qualification and a faster Return-on-Investment.

Share on LinkedInShare on FacebookTweet about this on Twitter

Related Posts

Visualizing Search Results in Solr: /browse and Beyond

Quantifying Performance Gains When Batching Indexing Updates to Solr

Mining Events for Recommendations

Preliminary Data Analysis with Fusion 2: Look, Leap, Repeat

Data Analytics using Fusion and Logstash

Top Posts

Understanding Transaction Logs, Soft Commit and Commit in SolrCloud

Faceted Search with Solr

Nested Queries in Solr

Posted in Blog Posts with tags #Big data #Hadoop #MapR

Your email address will not be published. Required fields are marked *