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

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

MeiliSearch is a powerful, fast, open-source, easy to use, and deploy search engine. The search and indexation are fully customizable and handles features like typo-tolerance, filters, and synonyms. It features include Search as-you-type experience, Full text search, Supports Synonym, Highly customizable, RESTfull API and lot more.

MeiliSearch - Ultra relevant, instant and typo-tolerant full-text search API

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

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