Home / Tech News / Featured Tech Reviews / QNAP TS-451D2-4G 4-bay NAS Review

QNAP TS-451D2-4G 4-bay NAS Review

Rating: 8.0.

QNAP's TS-451D2-G4 is a dual-core powered, 4-bay NAS aimed at home and SOHO users. It features DDR4 memory, 4K/60Hz HDMI 2.0 output, real-time transcoding and AES-NI encryption. Priced around the £440 mark, we find out if it is worth buying.

 

At the heart of the TS-451D2 is an Intel Celeron J4025, a dual-core CPU that is rated at 2.0GHz (boosting up to 2.9GHz). The NAS is available in two versions, the D2-4G (the system we are looking at here) with 4GB of DDR4-2400 memory and the D2-2G with 2GB of memory. The NAS supports a maximum of 8GB of memory via the two SO-DIMM slots so if you need to upgrade to more memory for any reason, the option is there. It also supports an AES-NI hardware encryption engine and hardware-accelerated transcoding.

QNAP quotes Sequential throughput performance for the TS-451D2 as up to 220MB/s for reads and up to 224MB/s for writes with both LAN ports being used in Link Aggregation mode. With a single Ethernet connection, the official figures are 113MB/s reads and 112MB/s writes.

QNAP back the TS-451D2 with a 2-year warranty but this can be extended up to 5 years by purchasing a warranty extension.

Physical Specifications

  • Processor: Intel Celeron J4025 2.0GHz (boosting up to 2.9GHz).
  • Memory: 4GB DDR4-2400.
  • Gigabit Ethernet Ports: 2.
  • Rear panel connectors: 2 x 1GbE RJ-45, 3 x USB 3.2 Gen 1 (Type-A), 1 x HDMI 2.0.
  • Front panel connectors: 1 x USB 3.2 Gen 1.
  • RAID support: 0, 1, 5, 6, 10, JBOD.
  • Cooling: Active, 1 x 120mm fan.
  • Drive Bays Supported: 4
  • Maximum hard drive size supported: 18TB.
  • Maximum Capacity: 72TB.
  • Internal File System support: EXT4.
  • Dimensions (D x W x H): 219.4 x 160 x 165.3mm.
  • Weight: 2.09kg.

Become a Patron!

Check Also

DLSS 5 NVIDIA

KitGuru Games: DLSS 5 misses the point

It would be hard to argue that NVIDIA’s DLSS technologies haven’t been a net positive to the PC space, with the machine-learning based upscaler successfully translating lower resolution inputs into a final image which is perceivably sharper while hogging fewer resources. Though somewhat more contentious, the next evolution of DLSS came in the form of Frame Generation, using ML in order to generate additional frames for high-refresh rate gaming. Both techniques can have their issues, but generally speaking they’ve allowed for more people to experience higher-end titles at increased frame rates. DLSS 5, however, takes a sharp pivot, with a very different end goal in mind than the performance-boosting versions that came before.