AI Database Convergence

"AI Database Convergence" examines how the integration of artificial intelligence is transforming traditional databases into autonomous, intelligent systems capable of optimizing performance, ensuring reliability, and supporting advanced AI workloads such as semantic search and real-time fraud detection. The book explores examples from industry leaders like Oracle, IBM, and Microsoft, highlighting recent advances like vector databases and self-improving query optimizers. It also delves into emerging frontiers such as reinforcement learning-based optimizers and compares current commercial solutions with experimental, self-learning architectures, offering a comprehensive view of the evolving landscape of enterprise data management.