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The OceanStor Pacific Series supports Erasure Coding (EC). EC provides 2.75x the disk space utilization of traditional three-copy mode for the highest rate in the industry at 91.6%, greatly reducing hardware, space, and energy consumption. This series can scale out to 4,096 nodes for flexible resource purchasing and deployment on demand. The decoupled storage-compute big data solution provides native HDFS, and is compatible with mainstream big data platforms and components for diversified data analysis and 30% lower TCO. The series provides precision purchasing with a sales model of available capacity1 for optimal investments.
Up to
for scalability on demand
Up to
disk space utilization
Reduced
TCO
Software algorithms are offloaded onto processors for hardware acceleration. The OceanStor Pacific Series employs an intelligent and lossless network that delivers a latency of less than 1 ms2 to quickly respond to critical workloads. A single bucket houses up to 100 billion objects without compromising performance to eliminate multiple buckets for large-scale applications. It also provides excellent I/O throughput for scenarios with a massive volume of small files. Its distributed architecture is fully symmetric for massive and linear performance scalability. Full-lifecycle storage system management predicts and processes resource usage and faults in advance for drastically streamlined O&M.
Up to
objects per bucket
As low as
stable latency
Fault disk prediction
in advance
Industry-leading distributed active-active technology3 across clusters enables service-level DR solutions at two sites with 100 km apart for load balancing, RPO = 0, RTO ≈ 0, and protection of core data assets. EC provides powerful redundancy protection to guarantee stable applications even if four nodes or four cabinets are simultaneously faulty. Comprehensive sub-health detection and pre-processing for systems accurately eliminate potential network, node, and component faults in advance. E2E data consistency verification provides high data availability for concurrent services.
Notes: 1. Actual capacity that can store service data; 2. Applicable to distributed block storage; 3. Applicable to distributed block storage
Hybrid Workloads | Multi-Protocol Interworking | High-Density Design
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