The speedup comes from a number of architectural and low-level performance optimizations in Manticore Search.
Manticore has a modern multithreading architecture with efficient query parallelization that fully utilizes all CPU cores. It supports real-time indexing - documents are searchable immediately after insertion, with no need to wait for flushes or refreshes.
It uses row-wise storage optimized for small to large datasets, and for even larger datasets that don’t fit into memory, there's support for columnar storage through the Manticore Columnar Library.
Secondary indexes are built automatically using the PGM-index (Piecewise Geometric Model index), which enables efficient filtering and sorting by mapping keys to their memory locations. The cost-based query optimizer uses statistics about the data to choose the most efficient execution plan for each query.
Manticore is SQL-first: SQL is its native syntax, and it speaks the MySQL protocol, so it works out of the box with MySQL clients.
It's written in C++, starts quickly, uses minimal RAM, and avoids garbage collection — which helps keep latencies low and stable even under load.
As for benchmarks, there's a growing collection of them at https://db-benchmarks.com, where Manticore is compared to Elasticsearch, MySQL, PostgreSQL, Meilisearch, Typesense, and others. The results are open and reproducible.
Manticore has a modern multithreading architecture with efficient query parallelization that fully utilizes all CPU cores. It supports real-time indexing - documents are searchable immediately after insertion, with no need to wait for flushes or refreshes.
It uses row-wise storage optimized for small to large datasets, and for even larger datasets that don’t fit into memory, there's support for columnar storage through the Manticore Columnar Library.
Secondary indexes are built automatically using the PGM-index (Piecewise Geometric Model index), which enables efficient filtering and sorting by mapping keys to their memory locations. The cost-based query optimizer uses statistics about the data to choose the most efficient execution plan for each query.
Manticore is SQL-first: SQL is its native syntax, and it speaks the MySQL protocol, so it works out of the box with MySQL clients.
It's written in C++, starts quickly, uses minimal RAM, and avoids garbage collection — which helps keep latencies low and stable even under load.
As for benchmarks, there's a growing collection of them at https://db-benchmarks.com, where Manticore is compared to Elasticsearch, MySQL, PostgreSQL, Meilisearch, Typesense, and others. The results are open and reproducible.