Open-source search database for full-text, vector, and hybrid search with real-time indexing and SQL.
Easy to use open source fast database for search
Manticore Search is an easy-to-use, open-source, and fast database designed for search. It is a great alternative to Elasticsearch.
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Introduction
❗Read recent blog post about Manticore vs Elasticsearch❗
What distinguishes it from other solutions is:
- It's very fast and therefore more cost-efficient than alternatives, for example Manticore is:
- 182x faster than MySQL for small data (reproducible❗)
- 29x faster than Elasticsearch for log analytics (reproducible❗)
- 15x faster than Elasticsearch for small dataset (reproducible❗)
- 5x faster than Elasticsearch for medium-size data (reproducible❗)
- 4x faster than Elasticsearch for big data (reproducible❗)
- up to 2x faster max throughput than Elasticsearch's for data ingestion on a single server (reproducible❗)
- With its modern multithreading architecture and efficient query parallelization capabilities, Manticore is able to fully utilize all your CPU cores to achieve the quickest response times possible.
- The powerful and speedy full-text search works seamlessly with both small and large datasets.
- Hybrid search combines full-text and vector retrieval in a single query for better relevance.
- Conversational search lets existing vectorized tables answer questions with KNN retrieval, conversation history, and LLM-backed responses through SQL
CALL CHATor the HTTP JSON/searchendpoint. - Row-wise storage for small, medium and big size datasets.
- For even larger datasets, Manticore offers columnar storage support through the Manticore Columnar Library, capable of handling datasets too big to fit in RAM.
- Performant secondary indexes are automatically created using the PGM-index (Piecewise Geometric Model index), which provides efficient mapping between indexed keys and their memory locations.
- The cost-based query optimizer uses statistical data about indexed data to evaluate and determine the most efficient execution plan.
- Manticore is SQL-first, utilizing SQL as its native syntax, and offers compatibility with the MySQL protocol, allowing you to use your preferred MySQL client.
- With clients available in PHP, Python, Python asyncio JavaScript, Typescript, Java, Elixir, Go, and Rust, integration with Manticore Search becomes easy.
- Manticore also provides a programmatic HTTP JSON protocol for more versatile data and schema management, with Elasticsearch-compatible writes support.
- Sharded tables transparently distribute reads and writes across multiple physical shards on one node or across a replication cluster.
- Built-in authentication and authorization secures MySQL, HTTP/HTTPS, distributed remote agents, and replication-related operations with users, bearer tokens, and fine-grained permissions.
- Built in C++, Manticore Search starts quickly and uses minimal RAM (around 40MB RSS for an empty instance), with low-level optimizations contributing to its impressive performance.
- With real-time inserts, newly added or updated documents are immediately accessible.
- Interactive courses are available through Interactive courses to make learning a breeze.
- Manticore also boasts built-in virtually synchronous multi-master replication using the Galera library and load balancing capabilities.
- Data can be synced from sources such as MySQL, PostgreSQL, ODBC, xml, and csv with ease.
- While not fully ACID-compliant, Manticore supports isolated transactions and binary logging for safe writes.
- Effortless data backup and recovery with built-in tools like manticore-backup, SQL BACKUP, and S3-compatible backup/restore support
Craigslist, Socialgist, PubChem, Rozetka and many others use Manticore for efficient searching and stream filtering.
Manticore Search was forked from Sphinx 2.3.2 in 2017.
More features
- Full-text search and relevance:
- Over 20 full-text operators and over 20 ranking factors
- Custom ranking
- Other search capabilities:
- Rich filtering functionality
- Fuzzy search
- Faceted search
- Geo-spatial search
- Hybrid search
- Vector search
- Conversational search
- Joining tables
- Spelling correction
- Autocomplete
- A wide range of functions for filtering and data manipulation
- Natural language processing (NLP):
- Stream filtering:
- High-availability:
- Sharded tables
- Data can be distributed across servers and data-centers
- Synchronous replication
- Built-in load balancing
- Security:
- Data safety:
- manticore-backup tool and SQL command BACKUP to back up and restore your data
- S3-compatible backup and restore
- Data storages:
- row-wise - requires more RAM, provides faster performance
- columnar - requires less RAM, still provides decent performance, but lower than the row-wise storage for some kinds of queries
- docstore - doesn't require RAM at all, but allows only fetching original value, not sorting/grouping/filtering
- Performance optimizations:
- Secondary indexes
- Cost-based optimizer determines the most efficient execution plan of a search query
- Data types:
- full-text field - inverted index
- int, bigint and float numeric fields in row-wise and columnar fashion
- multi-value attributes (array)
- string and JSON
- on-disk "stored" for key-value purpose
- Integrations:
Installation
Quick install
For Linux and macOS with Homebrew, use the one-line installer:
curl https://manticoresearch.com | sh
It detects Debian/Ubuntu/Mint, RHEL/CentOS/Amazon/Oracle/Fedora-like RPM systems, and macOS with Homebrew. It configures the official Manticore repository when needed, installs manticore, starts the service when supported, and prints the result.
Common commands:
curl https://manticoresearch.com | sh -s help
curl https://manticoresearch.com | sh -s list-versions
curl https://manticoresearch.com | sh -s version 25.0.0
curl https://manticoresearch.com | sh -s dev
curl https://manticoresearch.com | sh -s upgrade
Docker
Docker image is available on Docker Hub.
To experiment with Manticore Search in Docker just run:
docker run --name manticore --rm -d manticoresearch/manticore && until docker logs manticore 2>&1 | grep -q "accepting connections"; do sleep 1; done && docker exec -it manticore mysql && docker stop manticore
You can then: create a table, add data and run searches. For example:
create table movies(title text, year int) morphology='stem_en' html_strip='1' stopwords='en';
insert into movies(title, year) values ('The Seven Samurai', 1954), ('Bonnie and Clyde', 1954), ('Reservoir Dogs', 1992), ('Airplane!', 1980), ('Raging Bull', 1980), ('Groundhog Day', 1993), ('<a href="http://google.com/">Jurassic Park</a>', 1993), ('Ferris Bueller\'s Day Off', 1986);
select highlight(), year from movies where match('the dog');
select highlight(), year from movies where match('days') facet year;
select * from movies where match('google');
Note that upon exiting the MySQL client, the Manticore container will be stopped and removed, resulting in no saved data, so use this way only for testing / sandboxing purposes.
Read the full instruction for the docker image for more details including our recommendations on running it in production.
Manual package installation
If you prefer explicit package-manager commands, use the manual instructions below or see the downloads page.
RPM repo for RHEL/CentOS/Amazon/Oracle/Fedora-like Linux
sudo yum install https://repo.manticoresearch.com/manticore-repo.noarch.rpm
sudo yum install manticore
or use dnf when available:
sudo dnf install https://repo.manticoresearch.com/manticore-repo.noarch.rpm
sudo dnf install manticore
APT repo for Ubuntu/Debian/Mint
wget https://repo.manticoresearch.com/manticore-repo.noarch.deb
sudo apt install ./manticore-repo.noarch.deb
sudo apt update
sudo apt install manticore
Homebrew on macOS
brew install manticoresoftware/tap/manticoresearch manticoresoftware/tap/manticore-extra
Windows
For WSL/WSL2, use the Linux installer inside the WSL distribution. For native Windows, see the Windows installation instructions.
Clouds
Documentation and community sites
- Documentation
- Interactive courses
- Manticore Community Forum
- Public Slack chat
- Public Telegram chat (En)
- Public Telegram chat (Ru)
- Bug tracker
Third-party integrations
- https://dev.tiki.org/Manticore-Search - TikiWiki CMS Groupware integration
- https://github.com/EvilFreelancer/laravel-manticoresearch - Laravel ManticoreSearch plugin
- https://www.mediawiki.org/wiki/Extension:SphinxSearch - extension for MediaWiki
- https://github.com/gordonbanderson/silverstripe-manticore-search - integration for SilverStripe
- https://drwho.virtadpt.net/archive/2022-05-13/combining-manticore-and-searx/ - integration for SearX
- https://github.com/dimv36/sphinxlink - Extension for PostgreSQL for running search queries and returning data as PostgreSQL tables
How we can support you
Should your company require any help - we provide full-cycle services in the areas of Sphinx and Manticore Search:
- Audit
- Support
- Consulting
- Development
- Training
❤️ How you can support Manticore Search
Manticore Search is an Open Source project with development made possible by support from our core team, contributors, and sponsors. Building premium Open Source software is not easy. If you would like to make sure Manticore Search stays free, here is how you can help the project:
License
Manticore Search is distributed under GPLv3 or later. Manticore Search uses and re-distributes other open-source components. Please check the component licenses directory for details.