Compared
SQLite plus embeddings is still SQL
sqlite-vec describes itself as "an extremely small, fast enough vector search SQLite extension" that stores and queries float, int8 and binary vectors in virtual tables, written in C, running wherever SQLite runs. Its README says it is pre-v1 and to expect breaking changes. It is a successor to sqlite-vss.
What that stack is
Those sentences are from the sqlite-vec README , fetched 30 September 2026. You create tables, insert embeddings you computed, and query them with SQL. That is a good design when the rest of the application is already SQL and you want nearest neighbours beside ordinary rows.
FluctlightDB is also embedded and also a directory, which is why the comparison comes up. The call is not SQL. experience() writes an engram with context, salience and an optional source. activate() recalls from a cue. checkpoint() swaps a generation. There is no virtual table to query, and there is no embedder bundled in.
When to pick which
Pick SQLite with an embeddings extension when you want SQL, a vector index you control, and you will write the retrieval yourself. Pick FluctlightDB when the thing being stored is an agent’s experience and you want the cue, the source and the checkpoint as the API. Neither choice is a score. The overview says the same about the other projects, and it has no benchmark column for this reason.