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Product Overview |
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The HPE 64GB DDR4 PC4-17000 memory module is designed to provide reliable and error-corrected memory performance for servers and workstations. It fits within enterprise hardware environments where stability and speed are required to meet intensive computing needs without compromising data accuracy. |
General Information |
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| Brand | HPE |
| Part Number | 726719-64G |
Technical Information |
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| Memory Capacity | 64GB |
| Memory Technology | DDR4 |
| Module Type | RDIMM |
| RAM Standard | PC4-17000 |
| Pin Count | 288-Pin |
| Error Correction | ECC |
| Rank | 2Rx4 |
| Voltage | 1.2V |
Performance |
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| Bus Speed | 2133MHz |
| Bandwidth | 17000 MB/s |
| Native Speed | 2133 MT/s |
Physical Characteristics |
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| Package | Kit of 4 x 16GB DIMMs |
| Weight | 5.00 |
| Condition | Refurbished |
Miscellaneous |
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| Eco Friendly | Yes |
| Compliance Standards | WEEE, RoHS, CE |
| Assembly Required | Yes |
Product Description |
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This HPE memory kit consists of four 16GB DDR4 modules designed to boost server performance and reliability. It’s built for use in enterprise-class servers and workstations where stability and error correction are critical. Professionals managing data centers and high-demand computing tasks often rely on this memory module. Key Features
This memory module is typically deployed in servers powering business applications, virtualization, and database management. Its role is crucial in maintaining uptime and ensuring the integrity of critical data in demanding workloads. |
Use Cases |
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The HPE 64GB DDR4 PC4-17000 ECC memory module is optimized for enterprise-grade servers where data integrity and uptime are critical. It is suited for environments requiring consistent memory performance under heavy loads, such as virtualization clusters or database servers handling large datasets. How It's Used:
By delivering error-corrected, high-capacity memory modules, this product aids IT teams in maintaining system stability and scalability. It supports diverse workloads, helping organizations manage increasing data demands without compromising operational continuity. |