In this session, we'll discuss how data is stored, retrieved, augmented and isolated for users, and how index types, quantization, multi-tenancy, sharding, and replication affect their behaviour and performance. We will also discuss vector databases' integration with AI models that can generate vectors, or use retrieved data to produce augmented, or transformed outputs. When you emerge from this deep dive, you will have seen the inner workings of a vector database, and the key aspects that make them different to your grandma's database.