DuckDB Extension for Filtered HNSW Vector Search with ACORN-1 and Binary Quantization
By
cigrainger
If you only eat one bagel today, this is the bagel.
Summary
This article describes a DuckDB extension called duckdb-hnsw-acorn that implements ACORN-1 pre-filtered HNSW search for vector similarity search. The extension addresses two key limitations of the upstream duckdb-vss extension: broken filtered search (WHERE clauses applied after index returns results) and lack of vector compression (vectors stored as full F32). The fork fixes both issues by implementing proper filtered HNSW search with ACORN-1 pre-filtering and adding RaBitQ binary quantization for vector compression, making it more memory-efficient for high-dimensional vector data.
Key quotes
· 5 pulledThe upstream duckdb-vss extension has two limitations: Filtered search is broken. WHERE clauses are applied after the HNSW index returns results, so SELECT ... WHERE category = 'X' ORDER BY distance LIMIT 10 often returns fewer than 10 rows.
No vector compression. Every vector is stored as full F32, so the index memory scales linearly with dimensions.
This fork fixes both: implements proper filtered HNSW search with ACORN-1 pre-filtering and adds RaBitQ binary quantization for vector compression.
A DuckDB extension for vector similarity search with filtered HNSW (ACORN-1) and RaBitQ binary quantization.
Fork of duckdb/duckdb-vss.
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