https://docs.cozodb.org/en/latest/releases/v0.6.html?ref=emergentmind
This is the first I have seen of a vector database combined with a logic language.
- You can now create HNSW (hierarchical navigable small world) indices on relations containing vectors.
- The vector search functionality is integrated within Datalog, meaning that you can use vectors (either explicitly given or coming from another relation) as pivots to perform unification into the indexed relations (roughly equivalent to table joins in SQL).
- Unification with vector search is semantically no different from regular unification, meaning that you can even use vector search in recursive Datalog, enabling extremely complex query logic.
- The index resides on disk as a regular relation (unless you use the purely in-memory storage option, of course). During querying, close to the absolute minimum amount of memory is used, and memory is freed as soon as the processing is done (thanks to Rust’s RAII), so it can run on memory-constrained systems.