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Product Overview |
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The IBM 7.86TB SAS 12Gb/s Read Intensive 2.5-Inch Solid State Drive offers large capacity and fast data handling tailored for environments with heavy read demands. It fits seamlessly into enterprise servers and storage systems where consistent, quick access to data is essential. |
General Information |
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| Brand | Lenovo |
| Part Number | 01LJ498 |
Technical Information |
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| Capacity | 7.68TB |
| Memory Technology | Enterprise Triple-Level Cell (eTLC) |
| Form Factor | 2.5-inch |
| Interface | SAS 12Gb/s |
| Hot Swappable | Yes |
| Hot Pluggable | Yes |
Physical Characteristics |
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| Weight | 3.00 |
| Condition | Refurbished |
Miscellaneous |
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| Eco Friendly | Yes |
| Compliance Standards | WEEE, RoHS, CE, FCC |
Product Description |
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This IBM 7.86TB SAS 12Gb/s solid state drive is built for environments that require high-capacity, reliable storage with fast access times. It’s often found in data centers and enterprise servers where large volumes of data are read frequently. Designed specifically for read-intensive applications, this drive suits businesses running databases, analytics, and virtualization workloads. IT professionals and system administrators rely on it for consistent performance and durability. Key Features
Typically deployed in enterprise server racks and storage arrays, this SSD plays a key role in delivering quick data access and improving overall system responsiveness. Its reliability helps minimize downtime, making it a practical choice for mission-critical systems. |
Use Cases |
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The 01LJ498 IBM 7.86TB SAS 12Gb/s Read Intensive SSD is ideal for enterprise environments requiring rapid data access with high reliability. It serves organizations managing large-scale databases, virtualization platforms, or analytics workloads where read performance is critical. How It's Used:
This SSD enables IT teams to maintain operational responsiveness and scale storage solutions without compromising on read performance. Its integration into rack deployments and storage arrays helps balance capacity with the demands of read-intensive applications. |