
QNAP 2U 8-Bay short-depth rackmount NAS/iSCSI IP-SAN. AMD Ryzen V1500B 4C/8T, 4GB RAM,Redundant PSU TS-873AEU-RP-4G-US
Price as of Sep 1, 2026
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Product Details
TS-873AEU-RP-4G-US KEY FEATURES 8 x 3.5"/2.5" SATA III Drive Bays 2 x M.2 2280 PCIe 3.0 x1 Slots 2.2 GHz AMD Ryzen V1500B Quad-Core 4GB DDR4 RAM Dual 2.5 Gigabit Ethernet Ports 10 Gb/s USB Type-C & Type-A Ports RAID 0, 1, 5, 6, 10, 50, 60, and JBOD Up to 590 MB/s File Transfer Speeds Dual Redundant 300W Power Supplies QTS or QuTS hero Operating System The compact 2U rackmount TS-873AeU-RP combines an AMD Ryzen V1000 series V1500B quad-core/eight-thread 2.2 GHz processor and dual-2.5GbE connectivity in one chassis. Compared to its previous generation, the TS-873AeU-RP is enhanced with two M.2 PCIe Gen3 x 1 ports for NVMe SSD cache acceleration or Edge TPU empowered AI image recognition. Cutting-edge hardware integrated with comprehensive software solutions makes the TS-873AeU-RP the preeminent choice to tackle resource-demanding applications and tasks, such as virtual machines or intensive multi-user access. The space-efficient short depth design of only 11.7 inches (297.4 mm) makes it easy to install in small media cabinets or places with a lot of cabling. The TS-873AeU-RP also features two redundant power supplies to ensure maximum system uptime. 2U SHORT DEPTH DESIGN FOR UP TO 38% REDUCTION IN SIZE The 2U rackmount TS-873AeU-RP has a short depth design of only 11.7 inches (297.4 mm), making it an excellent choice for smaller racks, wall-mount AV rack cabinets, and network rack cabinets. The space saved by the short depth design can be reserved for cabling or ventilation. The TS-873AeU-RP is space-saving for flexible deployment and is especially suitable for multiple locations and applications including offices, audiovisual rooms, and security surveillance recording. TWO M.2 PCIE SLOTS FOR SSD CACHING AND ACCELERATED AI-POWERED IMAGE RECOGNITION The 8-bay TS-873AeU-RP is equipped with two M.2 PCIe Gen3 x 1 slots, enabling cache acceleration or SSD storage pools for improved performance, or Edge TPU for AI image recognition.



