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HPE Alletra Storage Server 4210 EDSFF Configure-to-order System

HPE Alletra Storage Server 4210 EDSFF Configure-to-order System

by HPE

MPNP78861-B21
Prices updated 19 May 2026

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Product Description

Are you looking for a storage server with exceptional performance and capacity to accelerate your AI-driven initiatives? The HPE Alletra Storage Server 4210 is specifically designed for data storage-intensive workloads that require peak performance. Offering configuration flexibility that optimizes thermal efficiency. it will power your essential data-driven initiatives. From data stores for AI and real-time data analytics to distributed and NoSQL databases. performance sensitive Software-Defined Storage. and data heavy hyperconverged infrastructure. it delivers the capabilities you need at ideal economics with trusted security and a cloud operating experience. This includes the option to consume as-a-service via HPE GreenLake enabling you to transition from owning and maintaining to simply utilizing. HPE Alletra Storage Server 4000 systems provide the data infrastructure needed for every data-driven organization.What is new supporting point:Support for up to three single-wide (SW) GPUs to unleash AI- driven data storage sever workloads.Multiple HPE cooling options increase performance and energy efficiency to support sustainability initiatives.HPE Integrated Lights-Out 7 (iLO 7) server management software with streamlined manageability through a redesigned GUI. Redfish API. and increased security via patented secure enclave technology.Configurable modular front storage for up to twenty direct connect EDSFF PCIe Gen5 SSDs. All-NVMe design with up to 315 GB/s bandwidth in a 1U standard form factor.Cloud operating experience built on the HPE GreenLake Cloud for simplified and automated lifecycle management including dramatically easier firmware management.Dual Intel Xeon 6 processors drive greater performance along with DDR5 memory at speeds of up to 6400 MT/s with up to 14%[1] more bandwidth for demanding data processing workloads.