From the VAST Data edition of November 1, 2026
StorageMath argues VAST's 99.9991% uptime and 10x-over-Kafka Event Broker claims lack the methodology needed for verification
StorageMath (independent storage-claims analysis site; authors not named) · Independent technical analysis of storage vendor claims · Global (applies to any VAST buyer)
- Publisher
- StorageMath
- Original publication
- 2026-01-02
- Source retrieved
- 2026-11-02
What happened
StorageMath examines VAST's claimed 99.9991% measured uptime (about 4.7 minutes a year) and Event Broker claims of a 10x+ advantage over Kafka on like-for-like hardware, later stated as 604% more throughput. It argues neither claim can be verified because VAST has not published definitions of downtime, sample size, exclusions, hardware and configuration, replication and acks settings, latency distributions, or reproducible scripts. It concludes the claims should be treated as marketing until methodology is published, while allowing the Event Broker may genuinely be faster.
Why it matters
Newly relevant because VAST's October 30 TCO blog extends the same Event Broker into a cost argument for cloud streaming. Public buyers evaluating VAST for state, local or campus data platforms can use this checklist of missing details to write evaluation criteria and demand reproducible evidence.
Evidence and measured results
Analytical commentary using arithmetic on the vendor's published figures; no new measurements, tests or customer data. Authors and funding are not disclosed; the site states it analyzes all vendors with equal scrutiny. It critiques performance and uptime claims, not the October 2026 TCO model specifically.
Limitations and uncertainty
Ten months old and polemical in tone; anonymous authorship; no independent test data. It references 2025 claims as reported by Blocks and Files; VAST may since have published more methodology (VAST's OpenMessaging test blogs were seen in search results but not inspected for this edition).
Put this evidence to work
Lighthouse Advisory interpretation, grounded in this source. Enriched 2026-11-02; this does not change the original publication date. Each role follows the same checklist so takeaways compare across sources.
Sales
Role takeaway
- Customer problem
- Buyers cannot compare storage or streaming platforms when vendor uptime and performance figures lack disclosed methods.
- Stakeholders
- Technical evaluation committee
- Procurement officer
- Enterprise architect
- Agency risk and resilience lead
- Discovery questions
- How will your evaluation weight vendor-reported uptime or benchmarks?
- Do you require reproducible test methodology from bidders?
- Which durability settings are mandatory for your event data?
- Value hypothesis
- Offering a transparent, customer-run benchmark can build trust faster than headline claims; this is interpretation, not a source finding.
- Potential engagement
- Help an evaluation team write measurable benchmark and availability criteria for a streaming or storage procurement.
- Unsupported claims
- That VAST's uptime or Kafka figures are false
- That VAST Event Broker is slower than Kafka
- Any measured result in either direction
Pre-sales engineering
Role takeaway
- Fit
- Applies to any evaluation of VAST Event Broker or VAST availability claims.
- Architecture and integration
- Benchmark both brokers on identical hardware and network with matched replication and acks settings, message sizes and partition counts.
- Prerequisites
- Representative message size and partition layout
- Agreed durability settings
- Identical test infrastructure
- Constraints
- No independent reproducible VAST Event Broker benchmark found
- Vendor test methodology not fully published per the analysis
- Security
- Not addressed by the source; resilience claims should be checked through failure-injection tests and contractual SLAs.
- Proof of value
- Publish configurations and raw latency distributions
- Measure sustained throughput over hours, not bursts
- Define and measure downtime versus degradation during node failure
Delivery
Role takeaway
- Work
- Translate vendor claims into customer-owned baseline and post-migration measurements.
- Dependencies
- Pre-migration baseline metrics
- Test harness (e.g., OpenMessaging benchmark)
- Change window for failure injection
- Ownership
- Customer platform engineering, with results reported to the IT governance board.
- Skills and adoption
- Teams need benchmarking discipline: matched settings, repeat runs and percentile reporting.
- Governance checkpoints
- Methodology approved before testing
- Results reviewed with configs attached
- Availability SLA written into contract
- Acceptance criteria
- Proposed: throughput and p99 latency measured under matched durability settings
- Proposed: measured failover time documented for node loss
- Risks
- Accepting vendor figures as baselines
- Comparing unmatched durability settings
- Burst results mistaken for sustained capacity
Implementation considerations
Lighthouse Advisory interpretation across the operating dimensions a public-sector buyer must settle before this evidence becomes a design. Each note answers the question under its heading for this specific source.
Architecture and integration
What must connect, and where does the AI sit in the workflow?
Durability settings (replication factor, acks), message size, partition counts and tail latency determine whether a broker comparison is like-for-like; any VAST Event Broker evaluation should fix these explicitly.
Governance
Who approves, reviews and stays accountable for outcomes?
Public procurement scoring should give no weight to unverified vendor uptime or benchmark figures and should require methodology disclosure or a customer-run proof of concept.
Security and privacy
What data, permissions and controls need testing?
Not directly addressed; availability claims bear on resilience planning for public-safety and emergency data streams, which should rely on contractual SLAs and tested failover rather than marketing uptime.
Accessibility and workforce
Who is affected, and what skills or accommodations follow?
Evaluation teams need staff able to run and interpret benchmarks; smaller agencies may need university or consortium help.
Procurement
What should contracts, pricing and exit terms secure?
Supports requiring methodology disclosure or bidder-supported proof-of-concept testing in RFP technical criteria.
Operating model
Which teams own the service once it runs?
Shifts trust from vendor marketing to customer-run measurement and contractual SLAs.
Publication history
- 2026-11-01VAST Data · Issue 042 resources
Stable resource ID: storagemath-vast-uptime-event-broker-claims-unverifiable-20260102