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ChipsThe story, in brief

Agentic workflows are making distributed, always-on databases nonnegotiable

Enterprise databases just became mission-critical AI infrastructure. Legacy architectures can't keep up.

Reporting by SiliconAngle 1 min brief
Illustration of independent geometric mechanisms passing paper tasks along branching amber tracks.
AI agents and the coordination of work.AI illustration by KeyNews
The KeyNews take

Why it matters

As agentic AI workloads scale into production, database infrastructure is shifting from operational afterthought to strategic competitive advantage. Organizations that don't upgrade their data platforms to handle real-time, distributed agent demands will bottleneck their AI deployments.

The key facts

4 to know

  1. Enterprise database infrastructure undergoing 'most consequential redesign in decades'

  2. Agentic AI workloads require elasticity legacy architectures lack

  3. Data platforms moving from afterthought to mission-critical for AI workflows

  4. Distributed, always-on databases becoming nonnegotiable for enterprise AI

Go to the source

SiliconAnglesiliconangle.com

Publisher excerpt: Enterprise database infrastructure is undergoing its most consequential redesign in decades, as agentic AI workloads demand a level of elasticity that legacy architectures were never built to provide. As AI becomes deeply embedded in mission-critical workflows, organizations are learning that the…
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