StorageMath

A recent Medium article titled “The AI Inventory Trap” argues that AI has made engineering so fast that downstream stations — code review, QA, security audit, product validation — now form the binding constraint on software delivery [1].

VAST Data has found its most cynical marketing angle yet: exploiting a genuine supply crisis to sell the same fraudulent data reduction math we’ve already debunked.

NetApp’s marketing for AFX makes a bold claim: the disaggregated ONTAP architecture delivers “all the performance benefits of parallel file systems” while being “simple, secure, and fully integrated” [1].

VAST Data has a lying problem.

VAST Data has made two extraordinary claims that deserve mathematical scrutiny: 99.9991% measured uptime and a 10x performance advantage over Apache Kafka.

In March 2025, Pure Storage announced FlashBlade//EXA with a headline claim: “more than 10 terabytes per second read performance in a single namespace.”

VAST Data commands a $30 billion potential valuation (August 2025 funding talks with CapitalG and Nvidia) based on $200M ARR and claimed 90% gross margins.

In December 2025, IBM announced acquisition of Confluent for $11 billion with the stated goal of creating a “Smart Data Platform for Enterprise Generative AI.”

In 2025, HPE accelerated its Alletra storage portfolio by adopting disaggregated shared-everything (DASE) architecture principles pioneered by VAST Data.

Hammerspace announced in November 2025 that it achieved #18 on the IO500 10-node production benchmark using “standard Linux, upstream NFSv4.2 client, and commodity NVMe flash.”

In 2025, DDN announced that its EXAScaler Lustre storage system ranks #1 on the IO500 benchmark and delivers “up to 11x more AI training sessions” per day compared to competitors.

GigaOm’s latest Primary Storage Radar positions Pure Storage and Hitachi Vantara as the top vendors, with Dell, NetApp, VAST Data, and HPE close behind [1].

Weka and HPE announced SPECstorage Solution 2020 benchmark results in January 2025, claiming the #1 ranking across all five workloads: AI_IMAGE, EDA_BLENDED, GENOMICS, SWBUILD, and VDA [1].

VAST Data has published benchmark results claiming substantial performance advantages over established solutions.

Pure Storage announced next-generation storage products at Pure//Accelerate in June 2025, including FlashBlade//EXA targeting AI and HPC workloads.

MinIO announced ExaPOD in November 2025, positioning it as “The Reference Architecture for Exascale AI” [1].

VAST Data’s Jan Heichler argues that AI workloads require fundamentally different parallel file system designs than “classical HPC” systems [1].

Scality CTO Giorgio Regni argues that as AI foundation models become “broadly available and increasingly interchangeable,” competitive advantage shifts from models to data pipeline infrastructure [1].

NetApp announced three major offerings at INSIGHT 2025: a disaggregated storage architecture called AFX, an “AI Data Engine” (AIDE), and enhanced ransomware protection [1].

Blocks and Files published an article by Chris Mellor on December 11, 2025, titled “The Nature of the VAST Data Beast” [1].

Cloudian announces “74 percent improvement in data processing performance” [1].

Dell ECS (Elastic Cloud Storage) and its software-defined successor ObjectScale claim “99.999999999 (eleven 9s)” data durability [1][2].

Cloudian HyperStore markets data durability ranging from “14 nines to 18 nines, or even 26 nines or higher” [1].