# Dell pushes AI factory, knocks rivals > Source: > Published: 2026-07-13 13:17:00+00:00 flash # Dell pushes AI factory, knocks rivals Jon Hyde, Dell’s Senior Director for Competitive Intelligence, has written three [more AI Factory blogs](https://www.blocksandfiles.com/ai-ml/2026/06/23/dell-data-gravity-is-more-than-byte-count/5259971) taking firm aim at competitors. New blog number one, “[Where AI Factories Hit Their First Ceiling](https://www.dell.com/en-us/blog/where-ai-factories-hit-their-first-ceiling/)” claims PowerScale used 72 percent less power, 80 percent less rack space, and 8x fewer backend switches than competitor reference designs. He says Nvidia-based AI Factories can hit power supply and space constraints because the GPU servers, storage and network switches can hit the limits of both in a datacenter building. Hyde asserts that “Storage-embedded AI stacks tend to require more backend network switches because of how their disaggregated architectures fan out across the fabric.³ More backend switches means more rack units consumed, more cabling, more cooling, more power drawn, before a single GPU has turned on.” Hyde’s example storage-embedded AI stack is VAST Data’s AI OS. He says the question that now matters is: “how much of this power budget is being spent on the storage layer we chose?” Dell says its PowerScale offering used 72 percent less power, 80 percent less rack space and 8x fewer backend switches to deliver equivalent Nvidia technology benchmark performance than Everpure and VAST Data. Hyde claims: “The comparison against VAST specifically landed at 41 percent less power and roughly 2x less rack space for comparable performance.” The comparison was based on Nvidia reference designs. Hyde positions his company's products head-on against VAST, and claims: “Some VAST materials cite roughly 77 percent lower power and 73 percent less rack space from Nvidia BlueField DPU offload, but those figures are improvements over VAST’s own pre-DPU baseline, not a head-to-head against an NVIDIA reference design that another vendor could reproduce.” New blog number two, "[It's Called a Database. It Doesn't Act Like One](https://www.dell.com/en-us/blog/it-s-called-a-database-it-doesn-t-act-like-one/),” Hyde opines that a platform that’s excellent at metadata and vectors and calls itself “a database” is making a category claim it can’t actually fulfill, because heavy, structured data which runs on tables, records and time-series, data “the business depends on, has different requirements that an index doesn’t satisfy.” He refers to theCUBE Research in a June 2025 analysis which described the VAST DataBase as a “distributed index” that “lacks the mature SQL optimizer, cost-based query planning, role-based governance and rich BI ecosystem that enterprises expect from Snowflake or BigQuery. The same analysis concluded that, despite impressive revenue growth, “VAST has not (yet) achieved a Databricks-style lakehouse, a Snowflake-grade cloud database, nor a hyperscaler data platform. This is not a dated or one-off critique — theCUBE reaffirmed the same assessment in February 2026.” Hyde brings in NAND Research on VAST which observes that, while VAST supports open standards like Apache Iceberg, “the underlying database engine is VAST-written,”⁴ an opinionated, vertically integrated implementation rather than a composable layer that plays nicely with the tools a modern data team already uses. NAND Research says the VAST model is closer to the HCI pattern than to the open-ecosystem pattern that NetApp, Dell, HPE and Everpure are all pursuing. Contrast with Dell where “Apache Iceberg as an open table format on ObjectScale. It means native interoperability with Databricks and Snowflake running against data stored on PowerScale and ObjectScale." The third new blog: "[The Blueprint for the Next Evaluation](https://www.dell.com/en-us/blog/the-blueprint-for-the-next-evaluation/),” presents five questions IT buyers should put to any AI data platform vendor, covering data gravity, sync-job/FTE cost, GPU utilization, facilities footprint and analytics stack compatibility, with Dell providing the best answers, in his view. Hyde says that, in an AI Factory storage supplier competing bid situation there are several aspects that matter: Evaluate for the data estate, not the demo. The vendor that wins is the one whose architecture survives contact with your real data gravity map. Price the plumbing, the GPUs and the building. Sync jobs, FTEs, GPU utilization and rack/power/switch counts are line items, not surprises. Respect the analytics stack the business already chose. Iceberg, Databricks, and Snowflake are the stack to build around, not workloads to migrate. He asserts a supplier’s “pitch deck is designed for the CIO’s job. The bill is paid by the facilities lead, the data engineering lead and the FinOps lead. Bring all three to every meeting.” Hyde lists five questions he claims expose which architectural philosophy the vendor is actually selling: What percentage of my data will realistically live inside your namespace in three years? ( [Post 1](https://www.dell.com/en-us/blog/it-s-not-a-storage-problem-it-s-data-gravity/))How many active sync jobs and FTEs will this architecture require at steady state? ( )[Post 2](https://www.dell.com/en-us/blog/when-architecture-fights-gravity-operations-pay-the-tax/)Will you publish TTFT, tokens per second, and cache hit rates on a current open–source model, reproducibly, with methodology and test conditions stated? ( )[Post 3](https://www.dell.com/en-us/blog/why-expensive-gpus-sit-idle/)Will you publish rack U, kilowatts, and backend switch count for a documented reference design at my scale, with sources? ( )[Post 4](https://www.dell.com/en-us/blog/where-ai-factories-hit-their-first-ceiling/)Can I run my existing Databricks and Snowflake workloads natively against my AI data, without re–platforming? ( )[Post 5](https://www.dell.com/en-us/blog/it-s-called-a-database-it-doesn-t-act-like-one/) Asked about these Dell blogs, a VAST Data spokesperson said: "We are aware. We don't comment on competitors." ##### Comment We can infer that Dell is feeling real competitive heat from VAST Data if its competitive intelligence guru puts out six blogs outlining detailed VAST critiques.