Rich search query syntax
Use lots of search operators and expressions to let your users find what they really need
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
Galera replication
Multi-master clustering for reverse search 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
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
- 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
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
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
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.
Recently we’ve remade our system threads. Since we’ve forked from Sphinx and earlier searchd had all system tasks made in an often-rise-up style. Each service worked in a dedicated thread which wakes up every 50ms and checks whether it has something to do or not. That means that even an idle daemon wakes 200 times a sec ‘just to check’ a task. Having 6 such tasks will make 1200 wakes a sec, and it became noticeable especially by clients on Amazon AWS which counts CPU usage. Those internal tasks were: (more…)