Graid Technology Inc. logo in front of a shiny blue decorative background.
News/PR
May 1, 2022

NEWS: ⏩ Starline Germany Announces NVMe Storage Solution with Western Digital and Graid Technology

"NVMe + SupremeRAID™ Makes It Possible: 23 Gigabytes Per Second."

Graid SupremeRAID™, as an NVMe RAID card, provides the maximum available SSD performance for your data center. This enables record-breaking NVMe SSD or NVMeoF performance via RAID without compromising data security or business continuity.

Featured on Starline.de

This breakthrough solution finally eliminates the traditional performance bottleneck of conventional RAID cards when paired with NVMe SSDs. It is also the world’s first NVMeoF RAID solution: It, therefore, protects not only directly connected SSDs but also those connected to the server via a JBOF (NVMe over Fabrics).

Read on Starline.de

Learn More

News & Resources

Join Graid Technology at the 2026 Dell Technologies Forum Shanghai on August 21! Discover how Dell × SupremeRAID™ solutions power AI from cloud to edge—from private AI and HPC clusters to edge AI and KV Cache offloading—with 2–10× higher storage performance, up to 80 GB/s per node, and up to 24× faster TTFT.
Don't miss our joint speaker session with Supermicro, where we'll walk through scaling approaches across every tier, from single-server to rack-scale to monolithic deployments, and show how dense NVMe GPU platforms paired with SupremeRAID™ turn SSDs into a high-performance, protected KV cache tier. If storage is becoming your AI infrastructure bottleneck, this is the session to catch. See you at FMS 2026!
Graid Technology has achieved an industry-first benchmark: 100 million IOPS on a protected RAID 5 volume for GPU-initiated I/O, built from 32 KIOXIA XD8 NVMe SSDs. The result shows that resilient NVMe storage can now operate at the scale that current and future AI deployments require, which is especially significant for environments that require both extreme performance and enterprise-class data protection. In benchmark testing with a WholeGraph training workload, [...]