Comparison of Three‑Replica and Dual‑RAID Distributed Storage Architectures

Distributed storage has become a core component of private clouds, public cloud platforms, server virtualization, and hyper‑converged infrastructures, offering block, object, and file services that increasingly replace traditional disk arrays.

The dominant three‑replica model, used by vendors such as Huawei, H3C, and Inspur, stores three copies of each data object across different OSDs. While this provides fault tolerance, it consumes significant network bandwidth during rebuilds, can cause TCP/IP retransmission delays, and suffers from the “slow‑disk” effect where individual HDDs become performance bottlenecks.

In contrast, the dual‑RAID approach (adopted by companies like Dao‑Entropy) combines local RAID within each node with a two‑copy distributed strategy across nodes. Local RAID handles immediate disk failures without triggering network‑wide reconstruction, preserving bandwidth and reducing latency.

Key advantages of dual‑RAID include:

Hardware‑failure isolation that avoids network‑level instability.

Automatic workload avoidance, ensuring uninterrupted service.

Minimal data latency during local repair, as no network traffic is consumed.

Strong fault‑tolerance: each node can survive multiple disk failures, surpassing the two‑disk limit of three‑replica systems.

Dual‑RAID also mitigates the “slow‑disk” problem by pooling storage resources, balancing workloads across all disks, and employing a two‑level cache (memory + NVMe) with adaptive algorithms to keep hot data in fast storage, thereby approaching all‑flash performance.

In summary, dual‑RAID offers superior performance, stability, and data reliability compared with the traditional three‑replica architecture, while also reducing operational complexity and labor costs.