White Paper

Choosing the Right Storage for Modern Workloads

AI workloads have outgrown traditional enterprise storage. Training runs span thousands of GPUs, agents write shared state in constant loops, and retrieval pipelines pull context from every direction at once. This white paper compares the four storage architectures competing to support modern AI infrastructure, using a real product from each category, so you can see exactly where each one holds up and where it falls short.

What You'll Learn

Where clustered dual-controller NAS and shared-nothing scale-out NAS start to buckle under AI-scale checkpoint writes, small-file fan-out, and rigid compute-capacity coupling.
Why parallel file systems and disaggregated, shared everything (DASE) architectures land on opposite ends of the flexibility-versus-operability spectrum.
How NetApp ONTAP, Dell PowerScale, Everpure FlashBlade, IBM Storage Scale, and the VAST AI OS stack up on data protection overhead, scale limits, and multi-protocol support.
Which architectural traits actually predict performance at AI scale, versus which ones just look good on a spec sheet.

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