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Product Overview |
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The HP 1.92TB Serial Attached SCSI (SAS) 24Gb/s Read Intensive 2.5-inch Solid State Drive provides a robust storage solution aimed at environments requiring quick, reliable access to large volumes of data. It fits well within enterprise server setups focused on read-heavy tasks and offers a good balance between capacity, speed, and endurance without unnecessary complexity. |
General Information |
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| Brand | HP |
| Part Number | P49031-K21 |
Technical Information |
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| Capacity | 1.92TB |
| Form Factor | 2.5-inch |
| Interface | SAS 24Gb/s |
| Hot Swappable | Yes |
| Hot Pluggable | Yes |
Physical Characteristics |
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| Weight | 1.10 |
| Condition | Refurbished |
Product Description |
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This HP 1.92TB Serial Attached SCSI (SAS) solid state drive is designed to handle demanding read-intensive workloads with reliable performance. It is commonly used in enterprise servers and data centers where fast access to large amounts of data is critical. Built for IT professionals managing databases, virtualization, and large-scale applications, this drive balances speed and endurance to optimize read-heavy operations. Key Features
You'll typically find this drive deployed in servers running mission-critical applications where read speed impacts overall system performance. It helps maintain fast data retrieval while supporting demanding workloads without compromising reliability. |
Use Cases |
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The HP 1.92TB SAS 24Gb/s Read Intensive 2.5-inch SSD is primarily deployed in enterprise data centers and high-performance computing environments where rapid access to large volumes of read-heavy data is crucial. It suits IT environments that require efficient storage solutions for workloads dominated by read operations, such as database querying and virtualization read caches. How It's Used:
This SSD improves operational efficiency by delivering consistent read performance and low latency in demanding server environments. Its compatibility with standard 2.5-inch bays supports scalable storage architectures, making it suitable for growth in data-heavy applications. |