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, 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. Another implication of Solr being able to return search results across a Hadoop cluster is that more data can be kept in Hadoop and not pretransformed for the sake of analytics. This means not having to anticipate the questions [to ask] before you load the data.
Solr will be rolled into HDP via a multistep process. The first phase involves making Solr available for customers on June 1 within a sandbox. After that, Solr will be integrated directly into the next release of HDP, although no release schedule for that has been announced yet. Later on, Hortonworks plans to do some work on hooking up Solr to Ambari, the management and monitoring component for Hadoop, for easier control of indexing speeds and alerting, among other aspects.
LucidWorks has also produced a version of Solr that's meant to join the ever-growing parade of open source or lower-priced products designed to steal some of Splunk's log-search thunder.