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Open source text search engine for big data and stream filtering

  • Filtering multi-language user generated data streams in real time
  • Indexing and searching over hundreds of terabytes of data
  • Search results grouping and faceting
  • High-quality search results ranking following best industry practices
  • Backend for search UI (eg. “Did you mean”, search phrase autocompletion, spelling correction etc.)

Rich search query syntax

Use lots of search operators and expressions to let your users find what they really need

Document
storage

Stores your original documents on disk compressed with no memory footprint and low-latency access

Built-in
SQL

The easiest and most intuitive way for designing queries which lets you learn the technology very fast

Real-time
indexes

RT indexes allows updates be instant available for searching

Replication

Synchronous replication for Real-time and PQ indexes

Powerful search ranking algorithm

Customize search ranking formula to promote things that really matter to your business

Geosearch
locating

Find objects close to others easily with built-in radius/polygon search functions

Flexible custom morphology

When you need you can customize morphology on character-by-character level

Built-in JSON support

If you prefer JSON based DSL over HTTP, Manticore supports it

Incredibly efficient, high-throughput stream filtering and high-quality filtering capabilities

Faceted
search

Built-in FACET operator lets you implement faceted search with just few lines of code

Built-in MySQL, Postgres and CSV support

Manticore Search can easily index from MySQL/Postgres/CSV/TSV out of the box. Just a matter of few lines in config file

ODBC and XMLpipe drivers for any data storage

Want to index data from other data storages? If it supports ODBC – not a problem at all. Xmlpipe driver covers everything else.

Tens of built-in functions and operators allow to do not only search, but analytic requests. We also support user-defined functions for any custom needs you may have

Built-in morphology support for most languages

In most cases you don’t need to think about search morphology at all

Works on any OS and in clouds

Works in Linux, Windows, OSX and in Docker

  •  To improve the relevance of our customers’ results we use Manticore Search as our data indexing solution, and Manticore Percolate Queries for real-time filtering of data in transit.  read more

    Jay Krall

    VP Product, SocialGist
  • We’ve chosen this product because of the high performance compared to alternatives, the ability to expand the functionality with help of udf-functions and the availability of SQL-like query language.read more

    Ivan Ivanov

    Team leader, OWOX
  • We contacted Manticore’s free support on Slack with questions related to migrating form Sphinx search.
    In 30 minutes we had the first reply, and a few days later our issue was resolved, and we now using Manticore search to perform over 5 billion queries every day. read more

    Alexander Sørnes

    Senior Developer, JMT Nordic
  • We opted to migrate to Manticore instead of upgrading Sphinx since Manticore is open source and better supported. We’re very happy with our decision. read more

    Josh Maines

    Buds Gun Shop
  • We were using Sphinx but lately was crashing quite often and as a result making our homepage completely broken … We now only have some quick performance drops, instead of a continuous failure read more

    Trang Ho & Gilles Bedel

    Tatoeba

Starting from v 3.2.0 Manticore Search introduced a new feature – Document Storage.

Historically Manticore Search was a text search engine which indexes texts but doesn’t keep the originals. A text is processed, transforming it from a plain string into special structures that form the full-text index, which allows fast text searching. In the result set, the user wasn’t receiving the original text, as recomposing it from the full-text index can be a complex process. In addition, indexation settings may include clauses that stop certain words from being indexed (like minimum word length or stopwords) which can make the reconstruction impossible.

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We are pleased to announce the release of Manticore Search 3.2.0. Downloads are available here and from the Manticore Github page. Docker image is available at Docker Hub.
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In Manticore 3.1.2 was added support for data encryption between your application or another client (curl, browser etc) and Manticore Search daemon. It’s important to have it enabled if you need to protect your data (queries, responses) from interception inside your local network and especially if you connect to Manticore Search over the internet. Setting it up requires using certificates. Below is just an example of how it can be done with self-signed certificates, there may be other options like purchasing certificates signed by a real CA.

In this tutorial, we will study how to use SSL in work with Manticore Search.

In case if you want to go through an interactive course, go here.

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