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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.
for scalability on demand
disk space utilization
Software algorithms are offloaded onto processors for hardware acceleration. The OceanStor Pacific Series employs AI Fabric for a lossless network and latency of less than 1 ms2 to quickly respond to critical services. A single bucket houses up to 100 billion objects without compromising performance to eliminate multiple buckets and application changing 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. AI powers storage lifecycle management to predict and process resource usage and faults in advance for drastically streamlined O&M.
objects per bucket
As low as
Fault disk prediction
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
Intelligent distributed storage with powerful scale-out capabilities offers on-demand provisioning of block, HDFS, object, and file storage and builds the trusted choice for mass, diversified data.
Scale-out file storage with fully symmetric distributed architecture stores hundreds of PBs and achieves TB/s throughput.
The transition from physical to virtual/cloud architecture requires distributed storage.
The OceanStor Pacific Series provides distributed storage resource pools with flexibility on demand for virtual/cloud environments to significantly improve resource deployment, expansion, and O&M efficiency.
Typical scenarios: Channel access clouds for Internet finance, agile development and testing, carrier cloud services in BOM domains, B2B cloud resource pools, e-government clouds, and industry clouds.
Big data analytics monetizes data and encourages enterprises to implement long-term storage. Longer storage of more data increases data volume from PBs to EBs and strains limited IT resources. As a result, cost optimization for mass data storage has become a critical issue.
The OceanStor Pacific Series provides a decoupled storage-compute big data solution for the mainstream platforms of big data analytics. This solution expands compute and storage resources on demand without changing applications for a more than 30% reduction in TCO.
Typical scenarios: Finance, carrier log retention, governments, and smart city projects.
High-performance computing (HPC) has been extensively applied to scientific research, oil and gas production, and genome sequencing. It has high requirements for computing and storage performance, scalability, and return on investment (ROI).
OThe OceanStor Pacific Series provides distributed, parallel file clients with industry-leading performance for HPC platforms. These clients are compatible with POSIX and MPI-IO to better adapt to HPC services. Automatic storage tiering optimizes architecture to increase both efficiency and cost-effectiveness.
Typical scenarios: Marine meteorology, genome sequencing, energy exploration, remote sensing satellites, and autonomous driving.
Video surveillance is vital to smart city projects with widespread application in resource waste awareness and facial, behavior, and vehicle recognition. Surveillance for a medium-sized city can generate dozens of PBs in video and image data.
The OceanStor Pacific Series connects to mainstream video surveillance platforms and provides enterprise-grade file storage with broad compatibility. It also uses high-density hardware and software with performance optimization to provide diversified video and image storage.
Typical scenarios: Smart city projects, smart rail transportation, and biometric recognition.
Object storage is gaining in popularity due to the increasing volume of Internet services, agile releases and cross-region access for mass data, cost-effective multi-temperature data storage, and growing backup and archiving requirements.
The OceanStor Pacific Series constructs storage resource pools for mass volumes of objects to provide online services with large throughput in real time, such as frequent hot access to Internet data, online audio and video data. The series also automatically implements long-term storage of cold data in Blu-ray media. This energy-efficient approach streamlines data access and reduces the storage costs of mass data.
Typical scenarios: Bank check images and dual-recording (sound and picture recording), medical images, Internet of Vehicles (IoV), and enterprise resource sharing.
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