Pushing PostgreSQL Limits: Engineering a Database Backbone for Billions of AI Interactions
Pushing PostgreSQL Limits: Engineering a Database Backbone for Billions of AI Interactions In the era of generative AI, where platforms like ChatGPT handle hundreds of millions of users generating billions of interactions daily, the database layer must evolve from a mere data store into a resilient, high-throughput powerhouse. PostgreSQL, long revered for its reliability and feature richness, has proven surprisingly capable of scaling to support millions of queries per second (QPS) with a single primary instance and dozens of read replicas—a feat that challenges conventional wisdom about relational database limits.[1][2] This post explores how engineering teams can replicate such scaling strategies, drawing from real-world AI workloads while connecting to broader database engineering principles, cloud architectures, and emerging tools. ...