Vector databases are suddenly everywhere — but what problem do they actually solve?In this video, I explain vector databases in simple terms, without math or buzzwords.Vector databases power modern AI systems by allowing them to understand meaning, not just exact words.Traditional databases work great for numbers, transactions, and records — but they fail when we ask questions based on context and similarity.In this episode of In Simple Terms, we break down:What vector databases areWhy traditional databases fall shortHow AI uses vectors to understand meaningReal-world examples from search, AI memory, and RAG systemsIf you’ve heard terms like embeddings, vector search, or retrieval-augmented generation and felt confused — this video is for you.00:13 Why Vector Databases Are Everywhere00:32 The Problem with Traditional Databases00:37 Exact Match vs Meaning01:03 Why AI Needs More Than Keywords01:31 What Is a Vector (In Simple Terms)01:56 Vector Space Explained02:21 Real-World Example (Customer Support)02:54 Why AI Uses Vector Databases03:34 Vector Databases & RAG03:44 Final Takeaway
