Vector distance functions

Applies to: Embedded ❌, Enterprise ✅

cosine_distance  distance  exact_distance  inner_product

Distance functions can evaluate arrays per row. Some deployment versions also recognize ORDER BY distance(vector, query_vector) LIMIT k over a table scan and plan it as vector search, with indexed or flat search as appropriate. Where available, exact_distance evaluates distance without that rewrite. Confirm the functions supported by your deployment and inspect SQL EXPLAIN; the function name alone does not guarantee an index-backed plan. See SQL vector search.

A third, optional argument is a comma-separated options string, and only distance and exact_distance accept one; cosine_distance and inner_product are plain two-argument functions. metric selects l2 (default, alias euclidean), cosine, or dot. nprobes and use_index only affect distance, since it’s the only one of the two that the index-search rewrite applies to in the first place — exact_distance is never rewritten into an index search, so passing it use_index/nprobes does nothing; use a plain distance call with use_index=false to force a flat scan instead:

SELECT id FROM documents
ORDER BY distance(embedding, ARRAY[0.1, 0.2, 0.3], 'metric=cosine,nprobes=20')
LIMIT 10

-- Force a flat scan, bypassing the index:
SELECT id FROM documents
ORDER BY distance(embedding, ARRAY[0.1, 0.2, 0.3], 'use_index=false')
LIMIT 10

SQL vector search

Server-version requirements and the supported ORDER BY query forms.

EXPLAIN

Confirm whether a query planned as an index-backed vector search.

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Vector distance functions

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SQL vector search

EXPLAIN

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SQL vector search

EXPLAIN

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