Skip to product information
1 of 1

Micron

MTA144ASQ16G72PSZ-2S6G1SG Micron 128GB DDR4 2666MHz PC4-21300 Reg ECC CL19 DIMM 1.2V Octal Rank Memory

MTA144ASQ16G72PSZ-2S6G1SG Micron 128GB DDR4 2666MHz PC4-21300 Reg ECC CL19 DIMM 1.2V Octal Rank Memory

Refurbished
Regular price $2,037.11 USD
Regular price Sale price $2,037.11 USD
Sale Sold out
Taxes included. Shipping calculated at checkout.
Quantity

The MTA144ASQ16G72PSZ-2S6G1SG Micron 128GB DDR4 2666MHz PC4-21300 Reg ECC CL19 DIMM 1.2V Octal Rank Memory is a high-performance, enterprise-grade memory solution designed to meet the demands of data-intensive applications. With a capacity of 128GB, this DIMM is ideal for servers and workstations that require large amounts of memory to run multiple virtual machines, databases, and other resource-hungry applications.

This Micron memory module operates at a speed of 2666MHz, which is faster than standard DDR4 memory, allowing for improved system responsiveness and reduced latency. The PC4-21300 rating indicates that this memory is optimized for systems that require high-bandwidth memory, making it an excellent choice for applications such as virtualization, cloud computing, and big data analytics.

The Reg ECC (Registered Error-Correcting Code) feature provides an additional layer of data integrity and reliability, making it an excellent choice for mission-critical applications where data corruption or loss can have severe consequences. With a CAS latency of 19, this memory module is designed to provide fast and efficient data access, ensuring that your system can handle demanding workloads with ease.

This 1.2V memory module is designed to be compatible with systems that support DDR4 memory at 1.2V, and its octal rank design allows for improved memory density and reduced power consumption. Whether you're building a new server or upgrading an existing one, the MTA144ASQ16G72PSZ-2S6G1SG Micron 128GB DDR4 memory module is an excellent choice for anyone who requires high-performance, reliable memory that can handle demanding workloads.

View full details