Typesense is an open source, typo tolerant search engine that is optimized for instant sub-50ms searches, while providing an intuitive developer experience. 
 
Features: 
<ul>
<li>Typo Tolerance: Handles typographical errors elegantly, out-of-the-box.</li>
<li>Simple and Delightful: Simple to set-up, integrate with, operate and scale.</li>
<li>Blazing Fast: Built in C++. Meticulously architected from the ground-up for low-latency (&lt;50ms) instant searches.</li>
<li>Tunable Ranking: Easy to tailor your search results to perfection.</li>
<li>Sorting: Sort results based on a particular field at query time (helpful for features like "Sort by Price (asc)").</li>
<li>Faceting &amp; Filtering: Drill down and refine results.</li>
<li>Grouping &amp; Distinct: Group similar results together to show more variety.</li>
<li>Federated Search: Search across multiple collections (indices) in a single HTTP request.</li>
<li>Scoped API Keys: Generate API keys that only allow access to certain records, for multi-tenant applications.</li>
<li>Synonyms: Define words as equivalents of each other, so searching for a word will also return results for the synonyms defined.</li>
<li>Curation &amp; Merchandizing: Boost particular records to a fixed position in the search results, to feature them.</li>
<li>Raft-based Clustering: Setup a distributed cluster that is highly available.</li>
<li>Seamless Version Upgrades: As new versions of Typesense come out, upgrading is as simple as swapping out the binary and restarting Typesense.</li>
</ul>

Typesense is an open source, typo tolerant search engine that is optimized for instant sub-50ms searches, while providing an intuitive developer experience. 

Typesense - Fast, typo tolerant search engine for building delightful search experiences

Elasticlunr.js is a lightweight full-text search engine in Javascript for browser search and offline search. Elasticlunr.js is developed based on Lunr.js, but more flexible than lunr.js. Elasticlunr.js provides Query-Time boosting and field search. Elasticlunr.js is a bit like Solr, but much smaller and not as bright, but also provide flexible configuration and query-time boosting.

Elasticlunr.js - Lightweight full-text search engine in Javascript for browser search and offline search

Quickwit is a distributed search engine built from the ground up to offer cost-efficiency and high reliability. By mere mortals for mere mortals, Quickwit's architecture is as simple as possible. Quickwit is written in Rust and built on top of the mighty tantivy library. It designed to index big datasets straight from object storage like AWS S3 in a stateless manner. 
<ul>
<li>Scalable distributed search: Host an arbitrary number of indexes on Amazon S3 and answer search queries in less than a second with a small pool of stateless search instances</li>
<li>Stream indexing: Ingest TB of data from your favorite distributed event streaming service. As of today, Quickwit supports Apache Kafka natively. The next releases will bring support for more platforms</li>
<li>Fault-tolerant architecture that won't lose data: Quickwit achieves exactly-once processing for indexing and safely stores your data on highly reliable object storage services such as Amazon S3</li>
<li>Cloud-native, easy to operate: Thanks to true decoupled compute and storage, search instances are stateless, add or remove search nodes within seconds</li>
<li>Sub-second full-text search on cloud / distributed storage: Quickwit Search re-designed indexing and index data structure to open it in less than 60ms on Amazon S3</li>
<li>Time-based sharding: Quickwit shards data by time when enabled. And you can use a second dimension to shard data thanks to our <a href="../../docs/design/querying">tags feature</a>. Time-based queries only access splits (a data piece of the index) that match the time range of the query which leads to significant performance improvements</li>
<li>Painless multi-tenant search: Create indexes for each tenant without hurting query performance. Or group tenants into one index and use tagging to prune irrelevant splits for your tenant query to improve significantly performance</li>
<li>Elasticsearch query language support</li>
<li>Decoupled compute and storage, stateless indexers &amp; searchers</li>
<li>Schemaless analytics</li>
</ul>

Quickwit is a distributed search engine built from the ground up to offer cost-efficiency and high reliability. By mere mortals for mere mortals, Quickwit's architecture is as simple as possible. Quickwit is written in Rust and built on top of the mighty tantivy library. It designed to index big datasets straight from object storage like AWS S3 in a stateless manner.

Quickwit - Fast and cost-efficient distributed search engine for immutable data

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

Searchdaimon is an open source search engine for corporate data and websites. It comes with a powerful administrator interface and can index websites and several common enterprise systems like SharePoint, Exchange, SQL databases, Windows file shares etc. It also supports many data sources (e.g., Word, PDF, Excel) and the possibility of faceted search, attribute navigation and collection sorting.

Searchdaimon - Enterprise Search

Yioop is an open source, PHP search engine capable of crawling, index, and providing search results for hundred of millions of pages on relatively low end hardware. It can index a variety of text formats HTML, RSS, PDF, RTF, DOC and images GIF, JPEG, PNG, etc. It can import data from ARC, WARC, Media-Wiki, Open Directory RDF. It is easily localized to many languages. It has built-in support for new feeds, discussion groups, blogs, and wikis. It also supports mixing indexes to create mash ups.

Yioop - Open Source Search Engine Software

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

YaCy (read "ya see") is a free distributed search engine, built on principles of peer-to-peer (P2P) networks. It is distributed on several hundred computers so-called YaCy-peers. Each YaCy-peer independently crawls through the Internet, analyzes and indexes found web pages, and stores indexing results in a common database which is shared with other YaCy-peers using principles of P2P networks.

YaCy - Decentralized Web Search

Open Distro for Elasticsearch is an Apache 2.0-licensed distribution of Elasticsearch enhanced with Enterprise Security, Alerting, SQL, Index Management, k-Nearest Neighbor Search, Performance Analyzer and more. 
 
It provides set of features to help you keep your data secure and stay compliant with regulations such as GDPR, HIPAA, PCI, and ISO. Whether you want to encrypt data in-transit, authenticate users against Active Directory, use Kerberos or JSON web tokens for single sign-on (SSO), or monitor and log any malicious access attempts, Open Distro for Elasticsearch has you covered.
 
It provides support to extract insights out of Elasticsearch using the familiar SQL query syntax. Use aggregations, group by, and where clauses to investigate your data. Read your data as JSON documents or CSV tables so you have the flexibility to use the format that works best for you

Open Distro for Elasticsearch is an Apache 2.0-licensed distribution of Elasticsearch enhanced with Enterprise Security, Alerting, SQL, Index Management, k-Nearest Neighbor Search, Performance Analyzer and more. 


Open Distro for Elasticsearch  - Elasticsearch enhanced with enterprise security, alerting, SQL, and more

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

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