Startups > Vast Data

Vast Data

VAST Data provides unified AI infrastructure combining storage, compute, and data management.
Series E $1.4B total Founded 2016 New York, New York 629 employees
VAST Data provides an operating system for AI that unifies compute, storage, and data management into a single platform designed for high-performance AI and analytics workloads. Built on DASE (Disaggregated Shared Everything) architecture, it eliminates data movement bottlenecks through components like VAST DataStore, DataBase, DataEngine, and InsightEngine with NVIDIA. The platform serves enterprises and GPU cloud providers running intensive AI training and inference, with over 25% of Fortune 100 companies adopting it for strategic AI initiatives.
Problem solved
Organizations waste resources moving data between siloed storage, compute, and analytics systems, creating bottlenecks that slow AI training, increase infrastructure costs, and complicate data pipelines.
Target customer
Enterprise organizations and GPU cloud service providers running large-scale AI training and analytics workloads; Fortune 100 companies with intensive data pipeline requirements.
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Founders
R
Renen Hallak
Founder & CEO
Former VP R&D at XtremIO (acquired by Dell EMC for $1B+), where he led architecture of all-flash arrays achieving 40% market share and $3B revenue; background in complexity theory and cryptography.
S
Shachar Fienblit
Co-Founder & Chief R&D Officer
Previously at Kaminario, an enterprise storage company focused on data infrastructure.
J
Jeff Denworth
Co-Founder
Previously at CTERA Networks, focused on data management and infrastructure.
Funding history
Series A $40M 2018 Led by Unknown · Unknown
Series B $40M February 2019 Led by Unknown · Unknown
Series C $100M April 2020 Led by Next47 (Siemens Investment Arm) · 83North, Commonfund Capital, Dell Technologies Capital, Goldman Sachs, Greenfield Partners, Mellanox Capital, Norwest Venture Partners
Series D $83M May 2021 Led by Unknown · NVIDIA, Tiger Global Management
Series E $118M December 2023 Led by Fidelity Management & Research Company · New Enterprise Associates (NEA), BOND Capital, Drive Capital
Series F $1B April 2026 Led by Drive Capital · Access Industries, NVIDIA, Fidelity Management & Research Company, New Enterprise Associates
Total raised: $1.4B
Industries
Artificial Intelligence (AI) Database Software
Pricing
Consumption-based pricing model where customers are billed based on actual storage usage and data managed, rather than fixed system sizes or hardware purchases. Scales with organizational needs.
Notable customers
Disney, Verizon, US Air Force, US Department of Energy, Booking Holdings, Agoda, Pixar Animation Studios, xAI (Colossus supercomputing cluster)
Integrations
NVIDIA InsightEngine (RAG service), NVIDIA GPU infrastructure, AWS, Unknown others
Tech stack
Vue.js (JavaScript frameworks) Nuxt.js (JavaScript frameworks) Microsoft ASP.NET (Web frameworks) Tailwind CSS (UI frameworks) VideoJS (Video players) Qualified (Live chat) Zendesk (Documentation) PWA Open Graph DocuSign Contentful (CMS) Sitecore (CMS) Magento (Ecommerce) Vercel Analytics (Analytics) VWO (Analytics) Linkedin Insight Tag (Analytics) HubSpot Analytics (Analytics) Hotjar (Analytics) Google Analytics (Analytics) Facebook Pixel (Analytics) HSTS (Security) Font Awesome (Font scripts) Node.js (Programming languages) PHP (Programming languages) Apple iCloud Mail (Webmail) Google Workspace (Email) MySQL (Databases) Twitter Ads (Advertising) Microsoft Advertising (Advertising) Google Tag Manager (Tag managers) Salesforce (CRM) Vercel (PaaS) Amazon Web Services (PaaS) HubSpot Cookie Policy Banner (Cookie compliance) Priority Hints (Performance)
Website
vastdata.com/
Competitors
Databricks
Focused on data warehousing and ML workflows; less emphasis on unified storage and compute infrastructure for AI at scale.
Snowflake
Cloud data warehouse with separation of compute and storage; lacks native AI-optimized infrastructure and high-performance storage focus.
NetApp
Traditional storage vendor with AI capabilities; uses conventional architecture rather than disaggregated shared everything for performance optimization.
Pure Storage
Flash storage provider; less integrated approach to unifying database, compute, and analytics in single platform.
Why this matters: VAST Data has scaled to $30B valuation in April 2026 (tripling from $9.1B in December 2023) backed by elite investors including NVIDIA, Fidelity, and Access Industries, reflecting massive market demand for unified AI infrastructure. The platform's adoption by 25%+ of Fortune 100 and critical infrastructure like xAI's Colossus supercomputer demonstrates it has become foundational to enterprise AI at scale.
Best for: Enterprise organizations and AI infrastructure providers managing large-scale training workloads who need unified data infrastructure to reduce costs, eliminate data movement bottlenecks, and accelerate time-to-insight.
Use cases
Large-scale AI model training
Organizations training LLMs and large AI models can eliminate data pipeline complexity by storing raw data, executing queries, and running compute in a unified system. xAI reported 50% reduction in total cost of ownership using VAST for its 200,000+ GPU Colossus supercomputing cluster.
Real-time analytics on unstructured data
Media companies like Disney and Pixar can perform analytics and render operations on massive video/image datasets without moving data between systems. Pixar has used VAST as its render platform since the film 'Soul'.
Multi-location data science infrastructure
Global enterprises like Booking Holdings can replicate and access distributed data across regions through VAST DataSpace's global namespace, enabling consistent AI model training without ETL complexity.
Alternatives
Databricks Choose Databricks if you prioritize SQL/ML lakehouse capabilities and prefer cloud-native flexibility over dedicated high-performance infrastructure optimization.
Snowflake Choose Snowflake if you need mature cloud data warehousing with established ecosystem; less suitable for GPU-intensive AI training workloads requiring unified compute and storage.
NetApp Choose NetApp for traditional enterprise storage with AI bolt-ons; lacks VAST's unified database-storage-compute architecture and disaggregated infrastructure design.
FAQ
What does VAST Data do? +
VAST Data provides a unified operating system for AI that combines storage, database, and compute into a single platform. Built on disaggregated shared everything (DASE) architecture, it eliminates data movement bottlenecks, reduces infrastructure complexity, and accelerates AI training and analytics workloads. The platform includes components like DataStore (storage), DataBase (DBMS), DataEngine (compute), InsightEngine (RAG), and AgentEngine (AI orchestration).
How much does VAST Data cost? +
VAST Data uses consumption-based pricing where customers are billed according to actual storage usage and data managed. Pricing scales with organizational needs rather than fixed system sizes. Contact VAST for enterprise pricing and custom packages.
Who uses VAST Data? +
Over 25% of Fortune 100 companies use VAST Data for strategic AI initiatives. Notable customers include Disney, Verizon, Pixar Animation Studios, Booking Holdings, xAI, the US Air Force, and US Department of Energy. It serves both enterprises with large-scale AI training needs and GPU cloud service providers.
How does VAST Data compare to Snowflake? +
While Snowflake is a mature cloud data warehouse separating compute and storage, VAST Data uniquely unifies storage, database, and compute in a single platform optimized for GPU-intensive AI workloads. VAST's DASE architecture eliminates data movement overhead, making it more suitable for large-scale AI training, whereas Snowflake excels at traditional cloud analytics and BI.
What makes VAST Data different from competitors? +
VAST's disaggregated shared everything (DASE) architecture physically separates compute nodes from storage via NVMe over fabric, enabling high-performance data access without bottlenecks. Its unified platform combines storage, database, compute, and AI orchestration in one system, reducing data movement complexity. Over 25% of Fortune 100 and major AI infrastructure providers rely on it; xAI achieved 50% TCO reduction using VAST.
Tags
AI infrastructure data storage unified data platform GPU optimization high-performance computing disaggregated architecture AI operating system