Jumper 2.0 is a collaborative community search platform that revolutionizes search by crowdsourcing knowledge management powered by a shared bookmarking engine. It is easily and quickly deployed into a community of practice that benefits users with complex and specialized search requirements. Jumper delivers universal search of any databases, flat files, fileshares, content systems, web pages, blogs and wikis, even people - through one simple search box. Jumper 2.0 collaborative search is an open source, web-based platform written in PHP and Javascript. Jumper uses peer and social-networking principles to tag and link distributed information resources to create an interactive, user-submitted, recommendation engine that allows you to search any content, media, or data regardless of format or location. Like Wikipedia, Jumper allows users to become contributors and editors of the service by creating, editing, and managing tag profiles. Jumper allows users to tag any information resource with keywords just like Delicious. Jumper delivers a comment and rating system that is similar to Amazon.

Jumper 2.0 is a collaborative community search platform that revolutionizes search by crowdsourcing knowledge management powered by a shared bookmarking engine. It is easily and quickly deployed into a community of practice that benefits users with complex and specialized search requirements. Jumper delivers universal search of any databases, flat files, fileshares, content systems, web pages, blogs and wikis, even people - through one simple search box.

Jumper - Collaborative search engine in PHP

Xapian is an Open Source Search Engine Library. It is written in C++, with bindings to allow use from Perl, Python, PHP, Java, Tcl, C# and Ruby. Xapian is a highly adaptable toolkit which allows developers to easily add advanced indexing and search facilities to their own applications. It supports the Probabilistic Information Retrieval model and also supports a rich set of boolean query operators. 

 It supports boolean, phrase and proximity, wildcard and synonym search. It is capable to perform related search by suggest more terms to the query text. Faceted search is supported. It has built-in filters to extract the content from various file formats like HTML, PDF, OpenOffice/StarOffice and lot more. 

It also provides support to index data from the database like MySQL, PostgreSQL, LDAP etc.

Xapian is an Open Source Search Engine Library. It is written in C++, with bindings to allow use from Perl, Python, PHP, Java, Tcl, C# and Ruby. Xapian is a highly adaptable toolkit which allows developers to easily add advanced indexing and search facilities to their own applications. It supports the Probabilistic Information Retrieval model and also supports a rich set of boolean query operators.

Xapian - Search Engine Library

MG4J (Managing Gigabytes for Java) is a free full-text search engine for large document collections written in Java. MG4J is a highly customisable, high-performance, full-fledged search engine providing state-of-the-art features (such as BM25/BM25F scoring) and new research algorithms. The main points of MG4J are Powerful indexing, Multi-index interval semantics, Virtual fields, Clustering and lot more. Release 5.0 has several source and binary incompatibilities, and introduces quasi-succinct indices.

MG4J (Managing Gigabytes for Java) is a free full-text search engine for large document collections written in Java. MG4J is a highly customisable, high-performance, full-fledged search engine providing state-of-the-art features (such as BM25/BM25F scoring) and new research algorithms. The main points of MG4J are Powerful indexing, Multi-index interval semantics, Virtual fields, Clustering and lot more. 

MG4J - Managing Gigabytes for Java

Terrier is a highly flexible, efficient, and effective open source search engine, readily deployable on large-scale collections of documents. Terrier implements state-of-the-art indexing and retrieval functionalities, and provides an ideal platform for the rapid development and evaluation of large-scale retrieval applications. Terrier can index large corpora of documents, and provides multiple indexing strategies, such as multi-pass, single-pass and large-scale MapReduce indexing.

Terrier - Information Retrieval Platform

The Lemur Project develops search engines, browser toolbars, text analysis tools, and data resources that support research and development of information retrieval and text mining software. The project is best known for its Indri search engine, Lemur Toolbar, and ClueWeb09 dataset. 

Lemur - Search Engine

Norconex HTTP Collector is a full-featured web crawler (or spider) that can manipulate and store collected data into a repositoriy of your choice (e.g. a search engine). It very flexible, powerful, easy to extend, and portable.

Norconex HTTP Collector - Enterprise Web Crawler

Nutch is open source web-search software. It builds on Lucene Java, adding web-specifics, such as a crawler, a link-graph database, parsers for HTML and other document formats, etc. Its main feature include
 <UL>
	<LI>Fetching, parsing and indexation in parallel and distributed</LI>
	<LI>Plugin support</LI>
	<LI>Ontology</LI>
	<LI>Clustering</LI>
	<LI>Distributed filesystem (via Hadoop)</LI>
	<LI>Link-graph database</LI>
	<LI>NTLM authentication</LI>
	<LI>MapReduce</LI>
	<LI>Many formats: plain text, HTML, XML, ZIP, OpenDocument (OpenOffice.org), Microsoft Office (Word, Excel, Powerpoint), PDF, JavaScript, RSS, RTF, MP3 (ID3 tags)</LI>
 </UL>

Nutch is open source web-search software. It builds on Lucene Java, adding web-specifics, such as a crawler, a link-graph database, parsers for HTML and other document formats, etc.

Nutch - Highly extensible, highly scalable Web crawler

Tantivy is a full text search engine library written in rust. It is closer to Lucene than to Elastic Search and Solr in the sense it is not an off-the-shelf search engine server, but rather a crate that can be used to build such a search engine.
 
Its features include: 
<ul>
<li>Full-text search</li>
<li>Configurable tokenizer (stemming available for 17 Latin languages with third party support for Chinese (<a href="https://crates.io/crates/tantivy-jieba" target="_blank" rel="nofollow">tantivy-jieba</a> and <a href="https://crates.io/crates/cang-jie" rel="nofollow">cang-jie</a>), Japanese (<a href="https://github.com/lindera-morphology/lindera-tantivy">lindera</a> and <a href="https://crates.io/crates/tantivy-tokenizer-tiny-segmenter" rel="nofollow">tantivy-tokenizer-tiny-segmenter</a>) and Korean (<a href="https://github.com/lindera-morphology/lindera-tantivy">lindera</a> + <a href="https://github.com/lindera-morphology/lindera-ko-dic-builder">lindera-ko-dic-builder</a>)</li>
<li>Fast (check out the <g-emoji class="g-emoji" alias="racehorse" fallback-src="https://github.githubassets.com/images/icons/emoji/unicode/1f40e.png">🐎</g-emoji> <g-emoji class="g-emoji" alias="sparkles" fallback-src="https://github.githubassets.com/images/icons/emoji/unicode/2728.png">✨</g-emoji> <a href="https://tantivy-search.github.io/bench/" rel="nofollow">benchmark</a> <g-emoji class="g-emoji" alias="sparkles" fallback-src="https://github.githubassets.com/images/icons/emoji/unicode/2728.png">✨</g-emoji> <g-emoji class="g-emoji" alias="racehorse" fallback-src="https://github.githubassets.com/images/icons/emoji/unicode/1f40e.png">🐎</g-emoji>)</li>
<li>Tiny startup time (&lt;10ms), perfect for command line tools</li>
<li>BM25 scoring (the same as Lucene)</li>
<li>Natural query language (e.g. <code>(michael AND jackson) OR "king of pop"</code>)</li>
<li>Phrase queries search (e.g. <code>"michael jackson"</code>)</li>
<li>Incremental indexing</li>
<li>Multithreaded indexing (indexing English Wikipedia takes &lt; 3 minutes on my desktop)</li>
<li>Mmap directory</li>
<li>SIMD integer compression when the platform/CPU includes the SSE2 instruction set</li>
<li>Single valued and multivalued u64, i64, and f64 fast fields (equivalent of doc values in Lucene)</li>
<li><code>&amp;[u8]</code> fast fields</li>
<li>Text, i64, u64, f64, dates, and hierarchical facet fields</li>
<li>LZ4 compressed document store</li>
<li>Range queries</li>
<li>Faceted search</li>
<li>Configurable indexing (optional term frequency and position indexing)</li>
<li>Cheesy logo with a horse</li>
</ul>

Tantivy is a full text search engine library written in rust. It is closer to Lucene than to Elastic Search and Solr in the sense it is not an off-the-shelf search engine server, but rather a crate that can be used to build such a search engine.

Tantivy - Full-text search engine library inspired by Lucene and written in Rust

mnoGoSearch for UNIX consists of a command line indexer and a search program which can be run under Apache Web Server, or any other HTTP server supporting CGI interface. mnoGoSearch for Unix is distributed in sources and can be compiled with a number of databases, depending on user's choice. It is known to work on a wide variety of the modern Unix operating systems including Linux, FreeBSD, Mac OSX, Solaris and others.

mnoGoSearch

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

The open source project strus provides a collection of C++ (C++98) libraries and command line tools for building a full-text search engine. The strus search engine can be build using any key value store database that provides an upper bound seek function for the stored key/value pairs. Currently there exists an implementation based on the LevelDB library.

Strus - Full text Search Engine in C++

It is a standalone search engine, meant to provide fast, size-efficient and relevant fulltext search functions to other applications. Sphinx was specially designed to integrate well with SQL databases and scripting languages. Currently built-in data sources support fetching data either via direct connection to MySQL or PostgreSQL, or using XML pipe mechanism (a pipe to indexer in special XML-based format which Sphinx recognizes). Official APIs for PHP, Python, Java, Ruby, pure C are included in Sphinx distribution. 
 Its feature includes: 
 <ul type="disc"><li>high indexing speed (upto 10 MB/sec on modern CPUs);</li><li>high search speed (avg query is under 0.1 sec on 2-4 GB text collections);</li><li>high scalability (upto 100 GB of text, upto 100 M documents on a single CPU);</li><li>provides good relevance ranking through combination of phrase proximity ranking and statistical (BM25) ranking;</li><li>provides distributed searching capabilities;</li><li>provides document exceprts generation;</li><li>provides searching from within MySQL through pluggable storage engine;</li><li>supports boolean, phrase, and word proximity queries;</li><li>supports multiple full-text fields per document (upto 32 by default);</li><li>supports multiple additional attributes per document (ie. groups, timestamps, etc);</li><li>supports stopwords;</li><li>supports both single-byte encodings and UTF-8;</li><li>supports English stemming, Russian stemming, and Soundex for morphology;</li><li>supports MySQL natively (MyISAM and InnoDB tables are both supported);</li><li>supports PostgreSQL natively.</li></ul>

Sphinix is free open-source SQL full-text search engine. How do you implement full-text search for that 10+ million row table, keep up with the load, and stay relevant? Sphinx is good at those kinds of riddles.

Sphinix - Search server

Manticore Search is an open source high performance full-text search oriented engine. It is a fork of Sphinx Search. Manticore Search is written in C++. It means speed and low resource consumption, it means you don’t have to worry about a garbage collector that suddenly makes a trouble.
<ul>
<li>Over 20 full-text operators and over 20 ranking factors, custom rankers</li>
<li>Advanced tokenization at character and word level</li>
<li>Morphology preprocessors</li>
<li>Real-time and offline indexes</li>
<li>JSON attributes</li>
<li>Distributed indexes</li>
<li>Built-in load balancer</li>
<li>Text highlighting and word correction</li>
<li>Geo search</li>
<li>Source data connectors for MySQL, PostgreSQL, MSSQL, ODBC, XML and CSV files</li>
<li>Connectivity: MySQL-based protocol, HTTP, native libraries</li>
</ul>

Manticore Search is an open source high performance full-text search oriented engine. It is a fork of  Sphinx Search. Manticore Search is written in C++. It means speed and low resource consumption, it means you don’t have to worry about a garbage collector that suddenly makes a trouble.

Manticore Search - High performance full-text search engine with SQL and JSON support

Heritrix is the Internet Archive's open-source, extensible, web-scale, archival-quality web crawler project. Heritrix is designed to respect the robots.txt exclusion directives and META robots tags, and collect material at a measured, adaptive pace unlikely to disrupt normal website activity. It provides web interface for operator control and monitoring of crawls. It stores content to ARC or ISO WARC aggregate/transcript format.

Heritrix is the Internet Archive's open-source, extensible, web-scale, archival-quality web crawler project. Heritrix is designed to respect the robots.txt exclusion directives and META robots tags, and collect material at a measured, adaptive pace unlikely to disrupt normal website activity.

Heritrix

ASPseek is an Internet search engine software developed by SWsoft.ASPseek consists of an indexing robot, a search daemon, and a CGI search frontend. It can index as many as a few million URLs and search for words and phrases, use wildcards, and do a Boolean search. Search results can be limited to time period given, site or Web space (set of sites) and sorted by relevance (PageRank is used) or date. ASPseek is optimized for multiple sites (threaded index, async DNS lookups, grouping results by site, Web spaces), but can be used for searching one site as well. ASPseek can work with multiple languages/encodings at once (including multibyte encodings such as Chinese) due to Unicode storage mode. Other features include stopwords and ispell support, a charset and language guesser, HTML templates for search results, excerpts, and query words highlighting.

ASPseek is an Internet search engine software developed by SWsoft.ASPseek consists of an indexing robot, a search daemon, and a CGI search frontend. It can index as many as a few million URLs and search for words and phrases, use wildcards, and do a Boolean search. Search results can be limited to time period given, site or Web space (set of sites) and sorted by relevance (PageRank is used) or date.

ASPseek

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