Vector databases are emerging as a crucial technology for AI-driven applications, allowing systems to understand and retrieve information based on semantic meaning rather than keywords. They store data as high-dimensional vectors, enabling efficient similarity searches that power everything from advanced recommendation engines to sophisticated generative AI models and RAG architectures.