VDURA Debuts V-ScaleFlow Tech, Cuts AI Storage Costs 60%
Today, VDURA announced Version 11.2 of its VDURA Data Platform. The latest version of their data storage and management platform for AI and high-performance computing (HPC) workloads introduces new capabilities that VDURA says boost performance while delivering 60% lower total cost of ownership (TCO) compared with flash-only competitors.
The release previews V-ScaleFlow, a new data flow management capability within the VDURA Data Platform that orchestrates the movement of data between hyperscale-class quad-level cell solid-state drives (QLC SSDs) and ultra-dense hard disk drives (HDDs). VDURA cites several factors that help achieve this reduction in cost with the introduction of V-ScaleFlow:
- V-Burst technology handles write-intensive AI checkpoints by absorbing data spikes and then writing sequentially to 128 terabyte (TB) QLC NVMe drives. This reduces flash requirements by more than 50% and lowers the cost per TB.
- V-ScaleFlow stores data on 30+ TB hyperscale HDDs to handle long-tail datasets and model artifacts. This use of hyperscale HDDs halves price and power consumption per petabyte versus all-flash alternatives.
In addition to these innovations, VDURA’s ease of use means that it has lower operational overhead costs that also contribute to the 60% TCO reduction: only one-half of a full-time-equivalent position is needed to manage 1 to 100 PB systems.
Version 11.2 also includes a native Kubernetes container storage interface (CSI) plug-in that simplifies multi-tenant Kubernetes-based deployments with zero-script persistent-volume provisioning and management. In addition, it offers end-to-end encryption to protect data in transit and at rest.
“V11.2 delivers the speed, cloud-native simplicity, and security our customers expect—while V-ScaleFlow applies hyperscaler design principles, leveraging the same commodity SSDs and HDDs to enable efficient scaling and breakthrough economics,” says Ken Claffey, CEO of VDURA.
VDURA was previously known as Panasas before rebranding in 2024. The company transitioned from a hardware-focused business model to being an AI and HPC data infrastructure software company operating under a software subscription-based business model.
The Tech Arena Take
VDURA’s announcement comes as enterprises face mounting pressure to manage escalating data volumes from AI applications and their associated costs. In our recent Data Center Infrastructure Requirements to Scale AI report, we covered how AI data centers require special design considerations due to their vastly greater computer and power requirements.
VDURA’s platform update directly addresses those challenges, and in doing so, benefits enterprises trying to balance AI adoption with controlling costs. This type of cost optimization will be crucial to keeping the expenses of AI infrastructure in check as businesses of all sizes, and budgets, look to adopt AI solutions.
Today, VDURA announced Version 11.2 of its VDURA Data Platform. The latest version of their data storage and management platform for AI and high-performance computing (HPC) workloads introduces new capabilities that VDURA says boost performance while delivering 60% lower total cost of ownership (TCO) compared with flash-only competitors.
The release previews V-ScaleFlow, a new data flow management capability within the VDURA Data Platform that orchestrates the movement of data between hyperscale-class quad-level cell solid-state drives (QLC SSDs) and ultra-dense hard disk drives (HDDs). VDURA cites several factors that help achieve this reduction in cost with the introduction of V-ScaleFlow:
- V-Burst technology handles write-intensive AI checkpoints by absorbing data spikes and then writing sequentially to 128 terabyte (TB) QLC NVMe drives. This reduces flash requirements by more than 50% and lowers the cost per TB.
- V-ScaleFlow stores data on 30+ TB hyperscale HDDs to handle long-tail datasets and model artifacts. This use of hyperscale HDDs halves price and power consumption per petabyte versus all-flash alternatives.
In addition to these innovations, VDURA’s ease of use means that it has lower operational overhead costs that also contribute to the 60% TCO reduction: only one-half of a full-time-equivalent position is needed to manage 1 to 100 PB systems.
Version 11.2 also includes a native Kubernetes container storage interface (CSI) plug-in that simplifies multi-tenant Kubernetes-based deployments with zero-script persistent-volume provisioning and management. In addition, it offers end-to-end encryption to protect data in transit and at rest.
“V11.2 delivers the speed, cloud-native simplicity, and security our customers expect—while V-ScaleFlow applies hyperscaler design principles, leveraging the same commodity SSDs and HDDs to enable efficient scaling and breakthrough economics,” says Ken Claffey, CEO of VDURA.
VDURA was previously known as Panasas before rebranding in 2024. The company transitioned from a hardware-focused business model to being an AI and HPC data infrastructure software company operating under a software subscription-based business model.
The Tech Arena Take
VDURA’s announcement comes as enterprises face mounting pressure to manage escalating data volumes from AI applications and their associated costs. In our recent Data Center Infrastructure Requirements to Scale AI report, we covered how AI data centers require special design considerations due to their vastly greater computer and power requirements.
VDURA’s platform update directly addresses those challenges, and in doing so, benefits enterprises trying to balance AI adoption with controlling costs. This type of cost optimization will be crucial to keeping the expenses of AI infrastructure in check as businesses of all sizes, and budgets, look to adopt AI solutions.
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