Dell 96GB DDR5 5600MHz RDIMM Three Rank

The Dell 96GB DDR5 5600MHz RDIMM Three Rank (SNP4Y1D1C/96G-5600) is a high-density registered dual in-line memory module engineered to meet the demanding memory bandwidth and capacity requirements of modern enterprise servers. Built on the DDR5 architecture, it operates at 5600 MT/s with an RDIMM (Registered DIMM) topology that uses an on-module register to buffer command and address signals, enabling stable operation in multi-DIMM-per-channel configurations typical of scalable server platforms. The three-rank organization maximizes addressable density on a single module, supporting large in-memory datasets without requiring additional DIMM slots.

DDR5 introduces on-die ECC (ODECC) as a baseline feature, providing an additional layer of data integrity at the DRAM cell level before system-level ECC is applied. The SNP4Y1D1C/96G-5600 carries a 288-pin DDR5 interface and is designed for compatibility with Dell PowerEdge server platforms that support DDR5 memory, including those based on 4th and 5th Generation Intel Xeon Scalable processors. Its validated integration with Dell OpenManage and iDRAC telemetry tools means memory health, temperature, and performance metrics are accessible through standard Dell systems management infrastructure.

With 96GB of addressable capacity per module, this RDIMM is well suited for environments where per-socket memory footprint is a primary constraint. Platforms populated with multiple units of this module can achieve aggregate memory capacities in the terabyte range, supporting memory-intensive virtualization stacks, large relational and in-memory databases, and AI/ML inference workloads that require rapid access to large model parameters and training datasets. Dell factory testing and validation ensure compatibility and reliability across supported PowerEdge configurations.

Ideal for

• Large-scale virtualization platforms requiring high per-host memory capacity to support dense virtual machine or container workloads without performance degradation
• In-memory database deployments such as SAP HANA, Oracle Database In-Memory, or Redis clusters where the entire working dataset must reside in DRAM for low-latency query response
• AI and machine learning inference servers where large model weights and feature vectors must be held in high-bandwidth memory to sustain throughput at scale
• High-performance computing (HPC) nodes running memory-bound simulation, finite element analysis, or computational fluid dynamics workloads that saturate memory bandwidth
• Enterprise data warehouse and analytics appliances processing large, complex queries across wide tables where memory capacity directly limits parallelism and scan speed
• Cloud-native and private-cloud infrastructure running memory-overcommitted hypervisor environments where maximizing DRAM per node reduces ballooning and swap overhead

Technical specifications

Available from Omnixon Global. Submit an RFQ and our team will confirm configuration and availability for your order.