Vector Databases Videos

Vector databases store embeddings and answer similarity queries at scale, which makes them foundational infrastructure for RAG, semantic search, and recommendation systems. Choosing between them involves genuine trade-offs — index types, filtering, hybrid search, cost — and the comparison videos and vendor deep dives collected here help make those trade-offs concrete before you commit to an architecture. This page aggregates Vector Databases videos from every creator we track, so you can compare how official labs, educators, and practitioners approach the same subject. Videos are a starting point, not the whole picture. Below the video feed you will find hand-picked learning guides that explain the underlying concepts in depth, popular open-source GitHub repositories where the ideas live as code, and the AI tools most closely associated with Vector Databases. We also surface the latest news coverage and research related to the topic, because a release video, its paper, and its press coverage each tell a different part of the story. Together they make this page a practical hub for going from "I watched a video about Vector Databases" to actually understanding and building with it.