Why Manticore Search Could Replace Elasticsearch: 10× Faster, Open‑Source DB

Manticore Search Introduction

Manticore Search is a high‑performance search engine written in C++, created in 2017 as a successor to Sphinx Search. It rewrites most of Sphinx’s code, fixes hundreds of bugs, and remains open source, offering modern, fast, lightweight full‑text search capabilities.

With over 3.7k GitHub stars and a growing user base, its developers claim it is a strong Elasticsearch alternative that may eventually replace the ELK stack.

Advantages

Extremely fast and cost‑effective; e.g., up to 182× faster than MySQL on small data.

29× faster than Elasticsearch for log analysis, 15× faster on small datasets, 5× on medium, 4× on large datasets.

Up to 2× higher throughput for data import on a single server.

Modern multithreaded architecture fully utilizes all CPU cores.

Powerful full‑text search for both small and large datasets.

Row‑level storage for various data sizes and columnar storage via Manticore Columnar Library for very large datasets.

Automatic secondary index creation, optimized query planner, and SQL‑compatible MySQL protocol.

Clients available for PHP, Python, JavaScript, Java, Elixir, Go, etc., plus an HTTP JSON protocol.

Fast startup, minimal memory usage, real‑time inserts, built‑in replication and load balancing, and support for data import from MySQL, PostgreSQL, ODBC, XML, CSV, with transaction‑like safety.

Companies such as Craigslist, Socialgist, PubChem, and Rozetka use Manticore for efficient search and stream filtering.

Usage

Installation instructions are available at https://manticoresearch.com/install/ and a Docker image can be pulled from Docker Hub:

https://hub.docker.com/r/manticoresearch/manticore/

Run Manticore in Docker:

docker run -e EXTRA=1 --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

Create a table, insert data, and perform searches:

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), ('Jurassic Park', 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');

Full documentation and source code are hosted at https://github.com/manticoresoftware/manticoresearch.