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Product Overview |
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The Dell 16GB DDR2 PC2-5300 667MHz RDIMM ECC Memory Module is a reliable server memory component designed to increase capacity and maintain system stability. It fits into Dell systems that require error-correcting memory to keep data accurate and operations smooth during intensive computing tasks. |
General Information |
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| Brand | Dell |
| Part Number | 311-9829 |
Technical Information |
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| Memory Capacity | 16GB |
| Memory Technology | DDR2 |
| Module Type | RDIMM |
| RAM Standard | PC2-5300 |
| Pin Count | 240-Pin |
| Error Correction | ECC |
| Voltage | 1.8V |
Performance |
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| Bus Speed | 667MHz |
| Bandwidth | 5300 MB/s |
| Native Speed | 667MHz |
| CAS | 5 |
Physical Characteristics |
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| Weight | 0.50 |
| 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 16GB DDR2 PC2-5300 memory module enhances system memory capacity while maintaining reliable operation through ECC technology. It is commonly used in servers and workstations where data integrity and uptime are critical. IT professionals and system builders often choose this module to upgrade or replace existing memory in compatible Dell systems. Key Features
This memory module is typically found in enterprise environments where servers handle large workloads or critical tasks. Its ECC function provides an extra layer of protection against memory errors, making it a trusted choice for maintaining system reliability over long periods. |
Use Cases |
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The Dell 16GB DDR2 PC2-5300 667MHz RDIMM ECC Memory Module is commonly deployed in legacy server environments requiring stable and reliable memory performance under heavy workloads. It is ideal for IT teams managing data centers or enterprise servers where error detection and correction are critical to maintaining uptime and data integrity. How It's Used:
By integrating error-correcting capabilities with registered DIMM stability, this memory module helps IT infrastructures sustain performance during intensive computational tasks while enabling smoother scalability within existing hardware frameworks. |