AI-native data platform that unifies storage, database, and compute at exabyte scale, serving large enterprise and research organizations
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<ul><li><strong>Pricing Model:</strong> Enterprise custom Capacity-based software subscription with hardware at manufacturer cost</li><li><strong>Packaging Model:</strong> Disaggregated software subscription with separate hardware procurement</li><li><strong>Credit Model:</strong> N/A</li></ul>
March 2, 2026
Last update:
<h3>Product Overview</h3><p>VAST Data is an enterprise data platform serving over 25% of Fortune 100 companies with $200 million in annual revenue and a $9.1 billion valuation. The company provides a unified data infrastructure combining storage, database, and compute capabilities built on their Disaggregated Shared-Everything (DASE) architecture. VAST's platform supports file, object, and block protocols while maintaining sub-millisecond latency at exabyte scale, positioning itself as AI-native infrastructure rather than traditional storage.<br />
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The company's Gemini commercial model separates software licensing from hardware procurement, allowing customers to purchase hardware at cost directly from manufacturers while subscribing to VAST's software platform.</p>
<h3>Key Features & Capabilities</h3><p>VAST Data offers a five-component integrated platform combining storage, database, and compute capabilities without edition-based licensing tiers.</p><ul><li>Core Platform Components: VAST DataStore (universal all-flash storage supporting NFS, SMB, S3, Kubernetes CSI), VAST DataSpace (global data fabric unifying edge-to-cloud), VAST DataBase (global database with sub-millisecond latency), VAST DataEngine (compute fabric for real-time processing), and VAST InsightEngine (AI pipeline automation and inference)</li><li>AI/ML Capabilities: Native vector search for AI applications, asynchronous parallel checkpointing maintaining 100% GPU utilization, support for millions of byte-level snapshots, and event-driven compute fabric with Python function execution</li><li>Data Management: 3:1 minimum data reduction guarantee (including encrypted/compressed data), immutable snapshots for ransomware protection, zero-RPO replication options, and cryptographic multi-tenancy with granular QoS controls</li><li>Security & Compliance: AES-XTS-256 encryption for data at rest, TLS 1.3 for data in flight, KMIP support for enterprise key management, fine-grained access controls with dynamic data masking, and compliance support for SEC, GDPR, FINRA, PCI DSS, HIPAA, and SOX</li></ul>
<h3>Pricing Model Analysis</h3><p>VAST Data employs a disaggregated subscription model that separates software licensing from hardware procurement. Software subscriptions are metered by storage capacity (terabytes) and compute resources (CPU cores), with 1-5 year contracts billed upfront. Hardware is purchased at manufacturer cost through certified resellers, eliminating traditional vendor markup.</p><div class="tableResponsive"><table cellpadding="6" cellspacing="0"><tr><th>Metric Type</th><th>What Measured</th><th>Why It Matters</th></tr><tr><td>Value Metric</td><td>Storage capacity and compute resources consumed</td><td>Aligns pricing with actual infrastructure utilization rather than arbitrary feature tiers</td></tr><tr><td>Usage Metric</td><td>Licensed capacity in terabytes with separate compute scaling</td><td>Enables independent scaling of performance and capacity based on workload requirements</td></tr><tr><td>Billable Metric</td><td>Software subscription fees plus hardware at manufacturer cost</td><td>Provides pricing transparency by eliminating vendor markup on commodity hardware</td></tr></table></div>
<h3>Customer Sentiment Highlights</h3><ul><li>“We've obtained a 3.5:1 data reduction ratio with the potential to hit 4:1 as we onboard more data. This allowed us to support more systems with a smaller footprint and provide larger home directory quotas for our users. - J.D. Maloney, Lead HPC Storage Engineer at NCSA”<b> <span class="pricingHiphenSymb"> - </span>NCSA Customer Story</b></li><li>“The ability to launch large containers across multiple nodes quickly is critical for our GPU workloads. VAST's performance allows us to keep those expensive GPUs fully utilized, which is a huge win for us. - J.D. Maloney, Lead HPC Storage Engineer at NCSA”<b> <span class="pricingHiphenSymb"> - </span>NCSA Customer Story</b></li><li>“The VAST Data Platform makes it simple for the Allen Institute to rapidly share and process data anywhere. These new hybrid cloud enhancements give our researchers and partners easy-to-use tools to build global AI pipelines that facilitate and accelerate our pursuit of new scientific discoveries. - David Feng, Director of Scientific Computing at Allen Institute”<b> <span class="pricingHiphenSymb"> - </span>Press Release</b></li><li>“Unbeatable price, easy management, and built-in analytics. Best multi-protocol solution (SMB/NFS/S3) besides ISILON/PowerScale. - Reddit user, r/storage community”<b> <span class="pricingHiphenSymb"> - </span>Reddit Discussion</b></li><li>“The way it's licensed means you can get more resilience for not much more money as it's on total capacity. - Reddit user, r/storage community”<b> <span class="pricingHiphenSymb"> - </span>Reddit Discussion</b></li></ul>
Metronome’s Take
<p>VAST Data employs a disaggregated subscription model that separates software licensing from hardware procurement. Software subscriptions are metered by storage capacity (terabytes) and compute resources (CPU cores), with 1-5 year contracts billed upfront for the full term. Hardware is purchased at manufacturer cost through certified resellers rather than bundled at vendor markup. This structure creates two independent cost levers: software subscription fees scale with capacity and compute needs, while hardware costs track manufacturer pricing directly.</p>
<p><strong>Recommendation:</strong> This capacity-plus-compute subscription model is commonly adopted by enterprise infrastructure platforms serving large-scale AI/ML workloads that require predictable economics and independent scaling of performance versus capacity. This pricing pattern bears similarity to how platforms like Snowflake and Databricks separate compute from storage pricing, though VAST differentiates through hardware disaggregation and guaranteed data reduction rather than consumption-based metering. Organizations with established hardware procurement relationships and large-scale AI training or inference workloads may find that transparent hardware pricing, included premium support, and elimination of forced refresh cycles can offer favorable total cost of ownership. Teams without existing reseller relationships may need to account for additional vendor management overhead, but the OpEx flexibility and independent scaling of capacity and compute can provide counterbalancing value for infrastructure-intensive deployments.</p>
<h4>Key Insights</h4><ul><li>
<strong>Hardware/Software Separation:</strong> Software subscriptions are decoupled from hardware procurement, allowing customers to purchase infrastructure components at manufacturer cost without vendor markup on commodity hardware. <p><strong>Benefit:</strong> Teams scale storage and compute independently without forced refresh cycles, reducing total cost of ownership.</p></li><li>
<strong>Guaranteed Data Reduction Economics:</strong> VAST contractually guarantees a 3:1 minimum data reduction ratio even on encrypted and compressed data through similarity-based deduplication. <p><strong>Benefit:</strong> Large-scale AI/ML deployments achieve predictable effective pricing with guaranteed capacity efficiency across all data types.</p></li><li>
<strong>Unified Platform Without Edition Tiers:</strong> All protocol support (file, object, block), security features, and data services are included in base licensing without edition-based segmentation. <p><strong>Benefit:</strong> AI/ML workloads access full platform capabilities from initial deployment without negotiating feature unlocks or edition upgrades.</p></li></ul>
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