As AI moves from experiments to execution, the real competition is no longer about smart models. It’s about who controls the data layer beneath them.
I write about the economics of AI.The real AI race isn’t about smarter models anymore. It’s about who can serve fast, reliable data toSnowflakeof Crunchy Data two weeks ago at its annual summit in San Francisco, it was a signal that the battle for AI dominance, which was once the domain of massive language models and advanced GPUs, was shifting straight into what many experts describe as the foundation of AI development: the database layer .
, noted in an interview, while Postgres was built for batch jobs, periodic queries and peak load measured in thousands, AI doesn’t work like that.“Retrofitting Postgres for real-time, agent-driven workloads exposes architectural limits. AI agents, copilots and real-time pipelines generate nonstop reads and writes. They require globally consistent data in milliseconds and expect systems to absorb failure without flinching,” Kimball said.are rethinking what the modern database needs to be.
Jeff Hollan, head of Cortex AI apps and agents, calls this the next frontier, noting that “the next generation of apps aren’t just data-hungry, but also reasoning-hungry.” That hunger for reasoning is why the database layer is now more critical for enterprises than ever before, Hollan said. As Raghunathan further explained, it’s an organizational issue. “Without clear vision and readiness at the infrastructure level,” he noted, “no amount of
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