Re:Comparison of vector databases
by ZephyrBlu on Monday July 31, 2023 @11:44AM
(#36944377)
Not a tutorial, but TLDR vector DBs are specialized DBs that store embeddings. Embeddings are vector representations of data (E.g. text or images), which means you can compare them in a quantifiable way.
This enables use cases like semantic search and Retrieval-Augmented Generation (RAG) as mentioned in the article.
Semantic search is: I search for "royal" and I get results that mention "king" or "queen" because they are semantically similar.
RAG is: I make a query asking, "tell me about the English royal family", semantically similar information is fetched using semantic search and provided as context to an LLM to generate an answer.
This enables use cases like semantic search and Retrieval-Augmented Generation (RAG) as mentioned in the article.
Semantic search is: I search for "royal" and I get results that mention "king" or "queen" because they are semantically similar.
RAG is: I make a query asking, "tell me about the English royal family", semantically similar information is fetched using semantic search and provided as context to an LLM to generate an answer.