When vector search isn't enough: hybrid graph+vector queries in VelesQL

"Find me the documentation for the function that handles authentication." Sounds simple. Embed the question, run a similarity search, return the top results. Except here is what pure vector search actually returns: [0.82] "Authentication is handled via JWT tokens with a 24h expiry." [0.79] "The login() function validates user credentials against the database." [0.71] "OAuth2 flow documentation for third-party integrations." [0.68] "Password hashing uses bcrypt with a cost factor of 12." All four results are about authentication. All four are semantically relevant. But none of them are the documentation for the actual function that handles it. The vector search found similar text, not the relationship between a function and its documentation. This is the fundamental limitation of pure vector search: it matches meaning, not structure. Why vectors alone fail on structured data Vector embeddings capture semantic similarity. "Dog" is close to "puppy." "Authentication" is close to "login." T