Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, dynamic clustering, database integration, and rich document (e.g., Word, PDF) handling. Solr is highly scalable, providing distributed search and index replication, and it powers the search and navigation features of many of the world's largest internet sites. Solr is written in Java and runs as a standalone full-text search server within a servlet container such as Tomcat. Solr uses the Lucene Java search library at its core for full-text indexing and search, and has REST-like HTTP/XML and JSON APIs that make it easy to use from virtually any programming language. Solr's powerful external configuration allows it to be tailored to almost any type of application without Java coding, and it has an extensive plugin architecture when more advanced customization is required. Its feature set include Rich Document Parsing and Indexing (PDF, Word, HTML, etc) using Apache Tika, An Administration Interface, Monitorable Logging, Fast Incremental Updates and Index Replication, Highly Scalable Distributed search with sharded index across multiple hosts, HTTP interface with configurable response formats (XML/XSLT, JSON, Python, Ruby, PHP, Velocity) Solrj is embedded solr. It provides Java based API and it takes care of constructing, parsing, sending and receiving HTTP request.

Solr is the popular, blazing fast open source enterprise search platform from the Apache Lucene project. Its major features include powerful full-text search, hit highlighting, faceted search, dynamic clustering, database integration, and rich document (e.g., Word, PDF) handling. Solr is highly scalable, providing distributed search and index replication, and it powers the search and navigation features of many of the world's largest internet sites. 

Solr - Blazing-fast, open source enterprise search platform

IndexTank search engine powers search in Reddit, Social bookmarking site. IndexTank is acquired by LinkedIn and released the project as open source. It includes features like Variables boosts, Facets, Faceted search, Snippeting, Custom scoring functions, Suggest, and Autocomplete. 
 Homepage: <A HREF="http://indextank.com/" target="_blank">http://indextank.com/</A>

IndexTank search engine powers search in Reddit, Social bookmarking site. IndexTank is acquired by LinkedIn and released the project as open source. It includes features like Variables boosts, Facets, Faceted search, Snippeting, Custom scoring functions, Suggest, and Autocomplete.

IndexTank - Search Engine powers Reddit

Sensei is a distributed data system that was built to support many product initiatives at LinkedIn, including the real-time faceted search in <A HREF="http://www.linkedin.com/signal/" target="_blank">LinkedIn Signal</A> and the news feed and tabs on the Homepage. Sensei is both a search engine and a database. It is designed to query and navigate through documents that consist of unstructured text and well-formed and structured metadata. 
 It supports Fast realtime updates, Complex query language and REST/JSON api, Hadoop integration and lot more.

Sensei is a distributed data system that was built to support many product initiatives at LinkedIn, including the real-time faceted search in LinkedIn Signal and the news feed and tabs on the Homepage. Sensei is both a search engine and a database. It is designed to query and navigate through documents that consist of unstructured text and  well-formed and structured metadata. Sensei is both a search engine and a database.

SenseiDB - Distributed, Realtime, Semi-Structured Database from LinkedIn

Bobo Browse is an information retrieval technology that provides navigational browsing into a semi-structured dataset. Beyond the result set from queries and selections, Bobo Browse also provides the facets from this point of browsing. It provides support to sort documents on fields that have multiple values. It is stable and used by LinkedIn.

Bobo - Faceted search library based on Lucene

LuMongo is a real-time distributed search and storage system based on Lucene. LuMongo is designed from the ground up to scale both vertically and horizontally across servers. LuMongo stores Lucene indexes directly into MongoDB. Documents can be stored natively into MongoDB. When stored natively document can be queried as normal out of MongoDB and use of Map-Reduce and the Aggregation Framework is possible.

LuMongo - Realtime Time Distributed Search

Compass provides real time searchengine built on top of Lucene. It is distributed, transcational, supports Spring MVC, integrates with ORM. Simple Compass provides a simple API for working with Lucene. If you know how to use an ORM, then you will feel right at home with Compass with simple operations for save, and delete & query. Compass provides google-style search, index updates as well as more advanced concepts such as caching and index sharding (sub indexes). Compass also uses built in optimizations for concurrent commits and merges. It provides support to map	Object, JSON, XML to search engine mapping. It allows storing the index with Data Grid products such as GigaSpaces, Coherence and Terracotta.

Compass is a real time searchengine. It is built on top of lucene. It is transactional, distributed, supports Spring MVC, integrates with Hibernate.    

compass - Searchengine built on top of Lucene

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Solr - Blazing-fast, open source enterprise search platform

IndexTank - Search Engine powers Reddit

SenseiDB - Distributed, Realtime, Semi-Structured Database from LinkedIn

Bobo - Faceted search library based on Lucene

LuMongo - Realtime Time Distributed Search

compass - Searchengine built on top of Lucene

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Projects

Solr - Blazing-fast, open source enterprise search platform

IndexTank - Search Engine powers Reddit

SenseiDB - Distributed, Realtime, Semi-Structured Database from LinkedIn

Bobo - Faceted search library based on Lucene

LuMongo - Realtime Time Distributed Search

compass - Searchengine built on top of Lucene

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