Recent content on 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]. The prescription is Theory of Constraints applied to a software org: cap upstream output, find where the constraint has moved, point AI at it, and…
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 . On January 27, 2026, VAST announced “VAST Amplify,” a program claiming to deliver “up to 6x or more effective capacity” from existing SSDs. Two weeks earlier, Blocks and Files ran a breathless piece about…
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]. Jeff Baxter, NetApp’s VP of Product Marketing, called it “a revitalization of NAS” that provides “all those benefits of a parallel file…
VAST Data has a lying problem. Their co-founder Jeff Denworth recently posted on LinkedIn claiming extraordinary data reduction ratios from customers migrating from “triplicated data lakes” to VAST DataBase. The numbers are impressive: 8x, 12.8x, and an eye-popping 29x capacity advantage. These claims are not merely misleading—they are deliberately constructed falsehoods designed to…
In March 2025, Pure Storage announced FlashBlade//EXA with a headline claim: “more than 10 terabytes per second read performance in a single namespace.” This sounds impressive until you start asking basic questions about what this number actually means. The “More Than” Problem “More than 10 TB/sec” is marketing speak for “we don’t want to tell you…
VAST Data has made two extraordinary claims that deserve mathematical scrutiny: 99.9991% measured uptime and a 10x performance advantage over Apache Kafka. Let’s examine what these numbers actually mean and whether they can be verified. If these claims sound familiar, you may have read our analysis of Cloudian’s absurd “26 nines” durability claim . VAST’s uptime…
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. This claim requires technical examination of both what IO500 measures and what DDN’s specific claims assert. What IO500 Measures The IO500 benchmark evaluates storage performance under HPC/AI workloads…
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.” The company positioned this as proving that standard protocols can deliver HPC-class performance without proprietary parallel file systems. The achievement is real. The framing requires clarification: pNFS v4.2…
In 2025, HPE accelerated its Alletra storage portfolio by adopting disaggregated shared-everything (DASE) architecture principles pioneered by VAST Data. However, HPE’s implementation diverges strategically from VAST’s approach in ways that reveal both competitive positioning and operational risk. HPE’s strategy: copy the architecture, not the lawsuit. VAST’s DASE…
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.” This framing requires technical examination. Confluent is event streaming infrastructure built on Apache Kafka. Understanding what Confluent does, what it does not do, and why IBM’s positioning is misleading requires…
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. The valuation assumes that support costs remain negligible as the company scales. This assumption conflicts with VAST’s actual system architecture. VAST has built a sophisticated, complex storage system. That sophistication creates…
MinIO announced ExaPOD in November 2025, positioning it as “The Reference Architecture for Exascale AI” [1]. The announcement describes a validated hardware configuration achieving 1 EiB usable capacity with 19.2 TB/s aggregate throughput at $4.55-4.60 per TiB-month. Unlike many vendor announcements that traffic in impossible claims, MinIO’s numbers appear mathematically sound.…
Pure Storage announced next-generation storage products at Pure//Accelerate in June 2025, including FlashBlade//EXA targeting AI and HPC workloads. The announcements included specific performance claims: FlashBlade//S R2 “performs up to 30% greater than competitors across critical workloads,” FlashBlade//EXA achieves “more than 10 terabytes per second of read performance within a…
VAST Data has published benchmark results claiming substantial performance advantages over established solutions. Their DataBase, a component of the VAST Data Platform, reportedly achieves 25% faster query performance than Apache Iceberg while using 30% less CPU, 20x faster needle-in-a-haystack queries with 1/10th the CPU, and 60x faster updates and deletions compared to object-based solutions…
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]. The results reportedly include “significantly lower latency—in some cases up to 6.5x lower than previous records” [2]. These are substantial claims. Unlike most vendor benchmark announcements,…
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]. The report evaluates 19 vendors across key features, emerging features, and business criteria. Pure Storage edges ahead on unweighted scores, followed by Dell and Hitachi Vantara in third. The graphic shows concentric circles with…
NetApp announced three major offerings at INSIGHT 2025: a disaggregated storage architecture called AFX, an “AI Data Engine” (AIDE), and enhanced ransomware protection [1]. The announcement follows a familiar pattern: a legacy storage vendor attempting to capture the AI halo while defending existing enterprise markets. The technology may be capable, but the claims warrant scrutiny. The…
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]. The conclusion: organizations should focus on “how you collect, shape, govern, and deliver data to those models.” Conveniently, Scality sells the object storage that Regni…
VAST Data’s Jan Heichler argues that AI workloads require fundamentally different parallel file system designs than “classical HPC” systems [1]. The framing positions traditional parallel file systems - Lustre, GPFS (Spectrum Scale), BeeGFS - as architectural relics unsuited for modern AI. VAST’s disaggregated, shared-everything (DASE) architecture, naturally, represents…
Cloudian HyperStore markets data durability ranging from “14 nines to 18 nines, or even 26 nines or higher” [1]. This appears in whitepapers, datasheets, and partner materials as a key competitive differentiator. The lower end of this range - 14 nines - represents legitimate engineering with standard erasure coding. The upper end - 26 nines - represents something else entirely: a…
Dell ECS (Elastic Cloud Storage) and its software-defined successor ObjectScale claim “99.999999999 (eleven 9s)” data durability [1][2]. This appears in technical FAQs, whitepapers, and product documentation as a key reliability metric. The architecture uses standard Reed-Solomon 12+4 erasure coding - well-understood technology with published mathematical foundations. The component…
Cloudian announces “74 percent improvement in data processing performance” [1]. Dell claims ObjectScale delivers “up to 2X greater throughput per node than the closest competitor” [2]. Both vendors publish specific numbers: 52,000 images per second, 230% higher throughput, 98% reduced CPU load. These benchmarks appear in press releases, blog posts, and sales materials as…
Blocks and Files published an article by Chris Mellor on December 11, 2025, titled “The Nature of the VAST Data Beast” [1]. The piece reads less like journalism and more like a press release translated into third-person prose. Mellor’s history of uncritical vendor coverage continues a troubling pattern where marketing narratives replace technical analysis. It presents…
StorageMath exists to cut through storage vendor marketing with mathematical truth. The Problem Storage vendors make bold claims: “Seven 9s uptime!” “Sub-millisecond latency!” “Survives 4 failures with only 2.74% overhead!” Some are accurate. Many are misleading. A few are mathematically impossible. Our Solution We apply mathematical rigor to every claim. We…
Compare erasure coding schemes, understand MDS properties, and see when advanced codes like Zigzag are feasible. The calculator provides real-time analysis of theoretical limits and practical trade-offs. Understanding MDS Codes Maximum Distance Separable (MDS) codes achieve the Singleton bound: with m parity shards, an MDS code can recover from ANY combination of m failures. Reed-Solomon is the…
VAST Data runs three different erasure coding schemes on the same hardware. Metadata uses 3× triplication requiring all replicas to acknowledge writes. Write buffers use N+2 double-parity erasure coding tolerating any 2 failures. The capacity tier employs proprietary LDEC with 146+4 wide stripes. This architectural choice creates operational asymmetries that affect system behavior during failures.…