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HP T9H98AAR 1TB PCI Express NVMe 3.0 x4 Multi-Level Cell HHHL SSD
- Capacity: 1TB
- Interface: PCI Express 3.0 x4
- Form Factor: HHHL (Half-Height, Half-Length)
- NAND Type: Multi-Level Cell (MLC)
- Protocol: NVMe
- Designed for high-speed storage solutions
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Product Overview
The HP T9H98AAR is a 1TB NVMe SSD designed for high-performance computing. It utilizes PCI Express 3.0 x4 interface for rapid data transfer speeds and Multi-Level Cell (MLC) NAND flash memory for a balance of performance and endurance. Its Half-Height, Half-Length (HHHL) form factor ensures compatibility with a wide range of servers and workstations.
Technical Information
| Capacity | 1TB |
| Interface | PCIe 3.0 x4 |
| Form Factor | HHHL |
Additional Specifications
| NAND Type | MLC |
| Protocol | NVMe |
Product Description
The HP T9H98AAR solid-state drive represents a significant leap in storage performance, leveraging the NVMe protocol over a PCI Express 3.0 x4 interface. This combination allows for substantially higher throughput and lower latency compared to traditional SATA-based SSDs. The drive's 1TB capacity makes it suitable for demanding applications, operating systems, and large datasets where quick access is paramount. Engineered with Multi-Level Cell (MLC) NAND flash, the T9H98AAR offers a robust balance between read/write performance, endurance, and cost-effectiveness. MLC NAND is known for its reliability and ability to withstand a considerable number of write cycles, making this SSD a dependable choice for enterprise environments. The Half-Height, Half-Length (HHHL) form factor is a standard add-in card design, facilitating easy installation into servers and workstations that may have limited space. This SSD is ideal for accelerating workloads such as virtualization, database operations, content creation, and high-performance computing. By reducing storage bottlenecks, the HP T9H98AAR enables faster application loading times, quicker file transfers, and improved overall system responsiveness, ultimately boosting productivity and efficiency in data-intensive tasks.
