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Data is cast as the essential asset in this age of the digital economy. Accordingly, enterprises are shifting away from mere data management, toward data operations, with big data playing an increasingly important role. However, traditional all-in-one big data solutions are plagued by a series of problems, brought on by explosive data growth — from high storage costs and prolonged scheduling to data silos — now making the decoupling of compute and storage resources more crucial than ever before.
Huawei OceanStor Mass Data Storage innovatively implements native Hadoop Distributed File System (HDFS) semantics at the storage layer. Doing away with the need to install plug-ins, reconstruct applications, or migrate data, the solution smoothly decouples storage and compute for big data, providing enterprises with superior storage, flexible data mobility, and simple management through storage-compute synergy.
Powered by Huawei OceanStor Mass Data Storage, the Decoupled Storage-Compute Big Data Solution has already been widely used in the finance, government, Internet, and telecom sectors. Indeed, in 2020, the solution won the Excellent Solution Award and the Best Data Infrastructure Solution Award from the China Association of Communication Enterprises, highlighting how OceanStor Mass Data Storage is leading industry innovation and accelerating digital transformation across industries.
• Storage-compute decoupling with on-demand resource expansion. • Elastic Erasure Code (EC) replaces multi-copy for 1.75x higher resource utilization, lowering Total Cost Ownership (TCO). • High density, with 120 disks taking up just 5U, slashing footprint by 62.5%, compared to other solutions.
• Resources on one storage device are shared through multiple protocols. • One data copy is accessed through multiple protocols, without the need for data migration. • Data tiering and automatic lifecycle management.
• Support for multiple fault domains, maintaining application continuity even if four nodes in each domain concurrently fail. • Fast data reconstruction and recovery. • Comprehensive sub-health detection and pre-processing prevent risks.
Enterprise Operation Analytics
Elastic EC replaces multi-copy for higher storage utilization at lower TCO.
Multi-protocol convergence for higher data analytics efficiency and faster computing.
Policing Cloud Big Data
Storage-compute decoupling, with global resource sharing, eliminates data silos and builds a converged, unified big data platform.
Financial Precision Marketing
Elastic scaling of storage and compute resources enables faster application rollout with support for rapid, user-centric innovations in the age of Bank 4.0.
e-Government Big Data
Storage-compute decoupling and automatic lifecycle management break down storage barriers and accelerate data mobility, building an e-government big data support platform for better governance, standards of living, and economic performance.
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