Big Data Search for Non-Technical Users is Offered in Hortonworks Data Platform 2.0

Hortonworks and LucidWorks have formed a partnership that allows Hortonworks users to access and analyze their data via Solr, the open source enterprise search platform from the Apache Lucene project.

The combination of Apache Solr and Hortonworks Data Platform (HDP) will benefit Hortonworks customers because Solr does not require complex script development to do searches, or access and identify patterns in data, and will therefore make big data available to more users within an organization.

The Hortonworks Data Platform is an open platform that enables enterprises to build and deploy Hadoop-based applications. LucidWorks, which provides a search development platform leveraging Apache Solr open source search, offers a simple interface that allows non-technical users to do advanced search. According to the companies, the combination of the solutions will enable users throughout an organization to easily access and gain insight from big data sets that were previously available only to developers, analyst and data scientists.

"Because Apache Solr doesn't require complex script development to do searches or access and identify patterns in data, our partnership with LucidWorks will dramatically accelerate the time to value for companies that are ready to make a major investment in big data," said Tim Hall, vice president of Product Management at Hortonworks. "The use of Solr will also democratize access to big data, which is critical to enabling companies to realize the full value of their information."

According to Tony Jewitt, vice president of Big Data Solutions at Avalon Consulting LLC, customers have been selecting these two technologies on their own and asking Avalon to integrate them.  “But now, this combination of LucidWorks and Hortonworks provides our clients with a seamless platform for deploying search-based applications running on HDP.  It's the perfect solution for analyzing social media, chat sessions, emails, documents and many other sources of big data."