When a RAG system retrieves, it embeds the query and asks the vector database for the nearest passages. Most production systems combine vector search with keyword search and re-ranking.
Vector search excels at fuzzy, semantic recall over unstructured text; a knowledge graph is the complement when explicit relationships and multi-hop reasoning matter.