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Patching LMDB: How We Made Meilisearch’s Vector Store 3x Faster

The Meilisearch team achieved a 333% performance improvement in their vector store by patching LMDB to enable concurrent indexing operations. They implemented a custom feature allowing write transactions to scale linearly with CPU cores, significantly boosting vector search capabilities. This optimization enhances their homemade HNSW implementation for approximate nearest neighbor searches.

Background

Meilisearch is a Rust-based search engine that uses LMDB as its underlying key-value store and implements HNSW for vector similarity search. Vector embeddings represent semantic meaning as high-dimensional vectors, where closer vectors indicate semantic similarity.

Source
Lobsters
Published
Mar 16, 2026 at 11:59 PM
Score
7.0 / 10