manticoresearch README

The project's README from github.com/manticoresoftware/manticoresearch. As one markdown file: README.md.

Manticore Search Logo

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.

manticoresoftware%2Fmanticoresearch | Trendshift

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License: GPLv3 or later GitHub Actions Workflow Status Twitter Follow Slack Docker pulls Newsletter Activity GitHub closed issues

Introduction

What distinguishes Manticore from other solutions is:

Craigslist, Socialgist, PubChem, Rozetka and many others use Manticore for efficient searching and stream filtering.

More features

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.

Documentation and community sites

Third-party integrations

How we can support you

Should your company require any help - we provide full-cycle services:

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:

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.

manticoresearch (manticoresoftware/manticoresearch)

Searching Database…

12.1K ·GitHub
Manticoresearch
What is this?Manticore Search is an open-source search database built for full-text, vector, and hybrid search with real-time indexing and SQL support. It's positioned as a fast, cost-efficient alternative to Elasticsearch.
Is this a database server I run, or a library I embed?It's a standalone database server with its own SQL dialect, MySQL-compatible wire protocol, and an HTTP JSON API. Official client libraries exist for PHP, Python, JavaScript, TypeScript, Java, Elixir, Go, and Rust to talk to it.
How do I get it running?On Linux or macOS with Homebrew there's a one-line installer that detects your OS, sets up the official repo, installs and starts the service. Alternatively, pull the Docker image from Docker Hub and run a container to try it out.
Do I need MySQL or Elasticsearch running alongside it?No, Manticore is a self-contained database — you just need a MySQL-compatible client (or the HTTP API) to talk to it, no external search engine required.
Is my data safe if something crashes mid-write?Manticore isn't fully ACID-compliant, though it supports isolated transactions and binary logging; backups are handled via the manticore-backup tool, SQL BACKUP, or S3-compatible backup/restore.
Does it run on Windows too, or just Linux/macOS?Native installers exist for Linux (Debian/Ubuntu, RHEL/CentOS/Fedora family) and macOS via Homebrew; on Windows you're expected to use WSL/WSL2 with the Linux installer, though there's also a native Windows installation path documented separately.
How much faster is it than Elasticsearch in practice?In the benchmarks cited, Manticore is around 3.85x faster than tuned Elasticsearch on 100M+ Hacker News comments and uses far less CPU and RAM for log ingestion workloads.
Can it do vector search alongside normal full-text search?Yes, hybrid search combines full-text and vector retrieval in a single query, and existing vectorized tables can even power conversational search with KNN retrieval and LLM-backed responses via SQL CALL CHAT or the HTTP /search endpoint.
What happens to my data if I just try it via Docker?The quickstart Docker container is meant for testing only: once you exit the MySQL client, the container stops and is removed, wiping any data you created.
Does it handle datasets too big to fit in RAM?Yes, its columnar storage (powered by the Manticore Columnar Library) is designed specifically for datasets larger than available RAM, trading some query speed for much lower memory use.
What are similar projects?xerj, typesense, meilisearch, hotdata-cli, doris, sonic, elasticsearch, hister
Which topics is it in?sql-client, bm25, full-text-search, search-engine, vector-search, semantic-search, search, mysql, sql, real-time, json, cpp
Creator
manticoresoftware
Size
108.6 MB
Stars
12.1K
Updated
CommitOct 16Releaserelease-29.9.0Sep 11
Age
9y
Commits · 90 Days