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GitHub - manticoresoftware/manticoresearch: Easy to use open source fast database for search | Good alternative to Elasticsearch now
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.
❗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:
- 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.
- 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.
- 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 and SQL BACKUP command
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.
- Full-text search and relevance:
- Other search capabilities:
- Natural language processing (NLP):
- Stream filtering:
- High-availability:
- Security:
- Data safety:
- 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:
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.
YUM repo for RHEL/Centos/Amazon/Oracle Linux
sudo yum install https://repo.manticoresearch.com/manticore-repo.noarch.rpm
sudo yum install manticore manticore-extra
APT repo for Ubuntu/Debian/Mint
wget https://repo.manticoresearch.com/manticore-repo.noarch.deb
sudo dpkg -i manticore-repo.noarch.deb
sudo apt update
sudo apt install manticore manticore-extra
brew install manticoresoftware/tap/manticoresearch manticoresoftware/tap/manticore-extra
See instruction here.
Documentation and community sites
Should your company require any help - we provide full-cycle services in the areas of Sphinx and Manticore Search:
- Audit
- Support
- Consulting
- Development
- Training
More details here
❤️ 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:
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.
RetroSearch is an open source project built by @garambo
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