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sqlite-vec vs Alopex DB
sqlite-vec, the SQLite vector search extension: vec0 virtual tables, metadata columns, and partition keys. Also explains how it differs from Alopex DB.
Updated: Oct 12, 2026
What sqlite-vec is
sqlite-vec is an extension that adds vector search to SQLite. It is written in pure C with no dependencies and runs anywhere SQLite runs. It is the successor to sqlite-vss.
How it works
- vec0 virtual tables: float, int8, and binary vectors are stored and queried in vec0 virtual tables.
- KNN search:
matchandkconditions on a vector column find the nearest vectors. - Non-vector columns: tables can have metadata, auxiliary, and partition key columns. Metadata column conditions filter inside a KNN query.
- Partition keys: the vector index is sharded internally by key, and an
=condition limits the search to one shard.
Main features
Packages exist for Python, Node.js, Ruby, Go, and Rust, and it also runs in the browser with WASM.
Limits
- sqlite-vec is pre-v1 and has breaking changes.
- A vec0 table can have at most 16 metadata columns. UNIQUE and NOT NULL constraints are not supported.
- Metadata conditions in a KNN query support only comparison operators. IS NULL, LIKE, GLOB, REGEXP, or functions give an error or incorrect results.
- Auxiliary columns cannot appear in the WHERE clause of a KNN query.
- Careless use of partition keys causes oversharding and slow KNN queries.
How it differs from Alopex DB
Both give SQL and vector search inside a database embedded in the application.
Alopex DB has a vector type and HNSW indexes in the core. Table rows and vectors are updated in the same transaction, and data lives in a single .alopex file.
Alopex DB ships with a vector type and HNSW indexes, so vector search starts without an extension. Compare for yourself in the quickstart.