manticoresoftware/manticoresearch

Open-source search database for full-text, vector, and hybrid search with real-time indexing and SQL.

What it solves

Manticore Search provides a high-performance, open-source alternative to databases like Elasticsearch for full-text search and data retrieval. It addresses the need for a search engine that is cost-efficient, fast, and capable of handling both small and massive datasets that may exceed available RAM.

How it works

Built in C++ for a small footprint and high speed, Manticore uses a combination of storage engines—row-wise for speed and columnar for massive datasets—to optimize performance. It is SQL-first and MySQL-compatible, allowing users to interact with it using standard SQL syntax. The system employs multi-threaded query execution and a cost-based optimizer to select the most efficient execution plans based on indexed-data statistics.

Who it’s for

Developers and organizations needing a scalable search infrastructure, specifically those looking for a faster, more resource-efficient alternative to Elasticsearch or those who want to integrate search capabilities into applications using SQL-compatible clients.

Highlights

  • Hybrid and Vector Search: Combines full-text and vector retrieval in single queries and supports KNN retrieval for conversational search.
  • Conversational Search: Enables LLM-backed responses and conversation history via SQL CALL CHAT or HTTP JSON endpoints.
  • High Performance: Benchmarked as significantly faster than MySQL and Elasticsearch in various workloads, with lower CPU and RAM usage.
  • Versatile Storage: Offers row-wise, columnar, and docstore storage options to balance speed and memory constraints.
  • Extensive Integration: Supports synchronization from MySQL, PostgreSQL, Kafka, CSV, and XML, with official clients for multiple languages including Python, Go, and Rust.

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