Unstructured data management platform for exabyte-scale hybrid deployments
Qumulo builds file storage and data management systems for enterprises managing petabyte-to-exabyte unstructured data across distributed environments. The tech stack—Python, Go, React, Kubernetes, Docker, and support for NFS, NVMe, and multi-cloud (AWS, Azure, GCP)—reflects a platform designed for portability and performance at scale. Active projects in federal compliance, healthcare toolkits, and high-performance ingest signal that Qumulo is consolidating around regulated verticals and real-time media workflows, while a hiring surge in support (28 roles) and sales (24 roles) suggests rapid customer acquisition and onboarding complexity.
Qumulo develops file data management software for enterprises with unstructured data workloads at scale—typically media production, healthcare, and federal agencies. The platform runs on customer-chosen infrastructure (on-premises, edge, or cloud) rather than proprietary hardware, addressing a core pain point in legacy storage solutions: platform lock-in. Deployment spans AWS, Azure, GCP, and on-prem Kubernetes environments. The company is based in Seattle, was founded in 2012, and currently operates across the United States, Canada, and Colombia. Active development focuses on healthcare and federal compliance toolkits, high-performance I/O for media editing, and architectural patterns for data sovereignty.
Python, Go, React, Node.js, TypeScript, Kubernetes, Docker, NFS, AWS, Azure, GCP, Salesforce, NetSuite, GraphQL, JWT, NVMe, SSD, and Cisco networking.
Seattle, WA. The company was founded in 2012 and is privately held with 201–500 employees.
Qumulo's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.