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Dell 82TVJ 1.6TB TLC PCIe NVMe U.2 2.5-In SSD
- Capacity: 1.6TB
- Interface: PCIe NVMe
- Form Factor: U.2 (2.5-inch)
- NAND Type: TLC (Triple-Level Cell)
- Designed for extreme performance workloads
- Low latency and high throughput
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Typically 1-2 handling + 3-7 transit days
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Product Overview
The Dell 82TVJ is a high-performance 1.6TB solid-state drive utilizing a PCIe NVMe interface with a U.2 form factor. Designed for extreme speed and low latency, it is ideal for the most demanding enterprise workloads, including AI, HPC, and big data analytics.
Technical Information
| Capacity | 1.6TB |
| Interface | PCIe NVMe |
| Form Factor | U.2 (2.5-inch) |
Additional Specifications
| NAND Type | TLC |
| Drive Type | SSD |
Product Description
The Dell 82TVJ 1.6TB SSD represents the pinnacle of storage performance, leveraging the PCIe NVMe interface for unparalleled speed and responsiveness. The U.2 form factor, also known as SFF-8639, allows this high-performance drive to be integrated into servers that support this standard, offering a significant upgrade path for storage-intensive applications. Its design is focused on delivering extremely low latency and high throughput, essential for cutting-edge enterprise computing. This drive utilizes TLC (Triple-Level Cell) NAND flash, providing a balance of high capacity, performance, and endurance suitable for demanding workloads. It is engineered for applications such as artificial intelligence (AI), high-performance computing (HPC), real-time analytics, and large-scale database operations where every millisecond counts. The NVMe protocol is specifically designed to take full advantage of the parallelism and low latency offered by flash memory. With a capacity of 1.6TB, the Dell 82TVJ offers substantial storage for high-demand environments. Its combination of PCIe NVMe interface, U.2 form factor, and advanced NAND technology makes it a critical component for organizations pushing the boundaries of data processing and analysis. This SSD is built to accelerate workloads, reduce bottlenecks, and enable faster insights from vast datasets.
