VAST Needs to Own Data Workflow

Diving deeper into

VAST Data

Company Report
storage vendors face increasing commoditization as hardware differentiation diminishes
Analyzed 7 sources

The real risk is that AI storage is starting to look less like a bespoke system sale and more like a certified module inside NVIDIA shaped stacks. When NVIDIA publishes validated designs and certifies a broad roster of storage partners, buyers can shortlist systems that are already approved for the same GPU environments. That makes raw throughput, latency, and protocol support easier to compare side by side, and puts more pressure on vendors like VAST to justify premium pricing with software layers above storage itself.

  • NVIDIA is widening the field. Its Enterprise AI Factory and AI Data Platform programs now frame storage as a certified component within a larger reference architecture, and NVIDIA lists VAST, WEKA, Pure Storage, Dell, NetApp, IBM, Nutanix, HPE, Hitachi Vantara, and DDN among storage partners. That standardization lowers switching friction for customers building AI factories.
  • The practical buying motion is changing. Instead of evaluating a storage array in isolation, an enterprise or cloud provider is increasingly buying a known good stack of GPUs, networking, software, and storage that has already passed NVIDIA performance tests. Pure has leaned into this with FlashBlade certifications and packaged reference designs, and Dell is doing the same with PowerScale and ObjectScale inside its AI Data Platform.
  • VAST's answer is to move the value higher in the stack. Its platform does not just hold files, it also lets teams search metadata, query data with SQL, and run preprocessing jobs where the data already lives. That matters because storage hardware is easier to substitute than a workflow where one system replaces storage, catalog, and analytics tools at once.

The next phase of AI infrastructure will reward vendors that own the data workflow, not just the storage box. As certified hardware options multiply, pricing power will shift toward companies that can turn stored data into something immediately usable for training, inference, and retrieval, and that is where VAST has to keep widening the gap.