Implementing Hybrid Semantic Search in SQLite with Binary Embeddings and Hamming Distance

This technical article demonstrates how to implement semantic search in SQLite using binary embeddings and Hamming distance, enabling hybrid search that combines traditional keyword matching with meaning-based retrieval. The author explains how to overcome SQLite's FTS5 extension limitations by using binary embeddings (compact vector representations) and Hamming distance calculations for similarity search, allowing developers to build hybrid search capabilities without relying on external vector databases.