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Last Updated: 08-21-2026 02:14 PM (UTC)

Manticore Search

With nearly 12,000 GitHub stars and a lineage tracing back to Sphinx Search, Manticore Search is the C++ search database that delivers the full-text, vector, and hybrid search capabilities of Elasticsearch at a fraction of the resource cost — starting in under a second and consuming just 40MB RAM for an empty instance. The SQL-first interface speaks the MySQL wire protocol, meaning mysql client, MySQL Workbench, and any MySQL-compatible driver connects natively without adapters, while the HTTP JSON API provides RESTful access for modern applications. Over 20 full-text operators handle proximity search, quorum matching, field-start and field-end constraints, MAYBE operators, and regex patterns, backed by stemming, lemmatization, stopwords, synonyms, wordforms, and advanced morphology in 70+ languages. Vector search with HNSW indexing enables semantic similarity queries, and hybrid mode combines keyword relevance with vector distance in a single ranked result set using a cost-based query optimizer. Real-time indexing delivers sub-second document availability after insert, sharded tables distribute data across nodes, and Galera-based synchronous replication ensures high availability. Conversational search via CREATE CHAT MODEL and CALL CHAT integrates LLM-backed responses with KNN retrieval and conversation history directly inside the database. Client libraries ship for PHP, Python, JavaScript, TypeScript, Java, Go, Rust, and Elixir. Columnar storage via the Manticore Columnar Library handles analytical workloads on large datasets. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. GPLv3 licensed.

Manticore Search
Manticore Search
Manticore Search
Manticore Search
Manticore Search

Benefits

  • Extreme Resource Efficiency and Speed
  • Start in under a second and serve queries from just 40MB RAM, running full-text search on minimal VPS configurations where Elasticsearch requires gigabytes of heap memory.
  • MySQL Protocol Native Compatibility
  • Connect using mysql client, MySQL Workbench, and any MySQL-compatible driver natively without adapters, writing standard SQL for search queries, indexing, and administration.
  • Unified Full-Text and Vector Search
  • Combine keyword relevance with HNSW vector similarity in a single hybrid query using a cost-based optimizer that ranks results by both textual match and semantic distance.
  • Built-In Conversational AI Search
  • Query vectorized tables with natural language via CREATE CHAT MODEL and CALL CHAT, integrating LLM-backed responses with KNN retrieval and conversation history natively.

Features

  • Advanced Full-Text Operators
  • Use over 20 operators including proximity, quorum matching, field-start, MAYBE, and regex with stemming, lemmatization, and morphology in 70+ languages.
  • Real-Time Document Indexing
  • Insert documents and make them searchable in sub-second latency with real-time tables that handle concurrent reads and writes without batch reindexing.
  • Sharded Tables and Replication
  • Distribute data across nodes with sharded tables and ensure high availability through Galera-based synchronous replication with automatic failover support.
  • Columnar Storage Analytics
  • Attach the Manticore Columnar Library for analytical workloads on large datasets with efficient compression and vectorized query execution on columnar data.
  • Multi-Language Client Libraries
  • Integrate with PHP, Python, JavaScript, TypeScript, Java, Go, Rust, and Elixir client libraries alongside the HTTP JSON API and MySQL protocol.