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LucidWorks, Hortonworks team up to be Hadoop’s search engine

4/04/2014 by


With Hadoop turning into a one-size-fits-all repository for data, an array of search solutions specifically for Hadoop have come to the fore over the past year. One of those contenders, LucidWorks, has joined with Hortonworks, one of the major distributors of Hadoop, to offer the LucidWorks edition of Hadoop search engine Solr as a reference architecture for searches on the Hortonworks Data Platform, or HDP.

Hortonworks made news earlier this week with word of a new edition (2.1) of HDP, released neck-and-neck with a rev of Pivotal’s own Hadoop-powered big-data offering. As before, the big advantage Hortonworks claims to bring is its pure open source roots: Anyone can pick up a copy of HDP and start working with it, no strings attached. No additional licensing fee is being charged for LuceneWorks Solr as part of HDP, either; the only charge is for support, per HDP itself.

Solr is based on Apache’s own Lucene project and adds many options not found in the original that ought to appeal to those building next-generation data-driven apps — for example, support for geospatial search.

The end-user advantages of Solr, according to Will Hayes, chief product officer for LucidWorks, lie in how it makes a broader variety of Hadoop searches possible for both less technical and more technical users. Queries can be constructed in natural language ways or through more precise key/value pairs.

“If you think about the precision approach [to Hadoop data],” said Hayes, “you have to know what you’re looking for. One of the things Solar will add on top of Hadoop is the ease of exploration of the data, a quick way for folks who perhaps have to do more precise access through SQL or Java APIs to explore the data in the lake, then be able to rapidly refine what they gain access to and what it means, and get better use for that data further down the road. They don’t have to start with a SQL or an API call.”

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