εταιρικά νέα για Huawei and the new enterprise storage market

AI is reshaping the enterprise storage market, prioritizing ultra-fast, efficient storage that supplies data for AI processing while delivering cyber-resilience, cutting data center footprint and lowering power consumption.

Organizations are rolling out generative AI large language models with natural language interfaces, plus agents capable of reasoning, intercommunication and initiating actions as quasi-digital employees. Both models and agents demand high-speed access to trusted data protected against malware and outages.

IDC states the enterprise storage market, overshadowed for two years by heavy server and GPU investments, now benefits from two mutually reinforcing tailwinds: enterprises refreshing storage infrastructure deferred during AI server rollouts, and fresh AI-driven storage demand from training pipelines, inference workloads and unstructured data activation use cases.

IDC adds component supply constraints, especially for NAND flash and DRAM, keep pushing system-level prices higher, lifting revenue growth beyond shipment volumes alone. The market is projected to maintain a positive trajectory with a 7.3% compound annual growth rate through 2030.

IDC ranks Huawei the world’s No.2 storage vendor. Huawei has built mature enterprise storage systems with OceanStor Dorado all-flash block, unified file and object storage, and OceanStor Pacific scale-out file, object and big data storage arrays.

It is a major industry player. For instance, Norway’s National Library is building a Norwegian-language LLM using in-house compute and over 2 petabytes of flash capacity across multiple all-flash arrays. This low-latency storage supports data pipelines and training preparation. Ruijin Hospital deploys OceanStor Pacific as a scale-out platform for a digital pathology data lake storing over one million scanned slides annually. The hospital’s multimodal RuiPath AI pathology model leverages this data with Huawei’s ModelEngine toolchain for data preparation, training and inference.

Gartner’s August 2026 Enterprise Storage Magic Quadrant places Huawei among the top 3 vendors. Huawei has featured in this Magic Quadrant for more than a decade. Gartner notes Huawei’s OceanStor Dorado all-flash storage, OceanStor Pacific storage and AI Data Platform target mission-critical OLTP, high-performance unstructured data and enterprise AI workloads. Huawei continues heavy investment in AI-native storage architectures including UnifiedBus networks, Context Memory Storage and vertically integrated high-density SSD hardware to reduce supply chain volatility.

The report’s analysts set out several strategic assumptions:

• --By 2029, consumption-based storage as a service (STaaS) will replace 50% of on-prem enterprise storage and data services capex, up from 25% in early 2026.
• --By 2029, over 80% of on-prem unstructured data will run on consolidated storage platforms instead of separate file and object products, rising from 50% in 2025.
• --By 2029, 70% of organizations will deploy purpose-built AI storage tiers for large-scale AI inference and retrieval-augmented generation (RAG), up from under 10% in 2026.
• --By 2029, all storage products will include cyberstorage capabilities focused on active defense beyond post-incident recovery, up from 25% in early 2026.
• --For 2027, I&O leaders must budget 250–300% of their 2025 storage spend to cover rising memory and storage costs driven by AI server and storage demand growth.

This final point aligns with IDC’s remarks and highlights the need for storage efficiency to limit costly NAND consumption.

Gartner analysts say the enterprise storage platforms market is undergoing unprecedented structural transformation driven by four major forces: extreme supply chain volatility and cost inflation, production-scale AI adoption, hypervisor replatforming, and cyber-data-resilient architectures. The traditional divide between monolithic high-end arrays and dual-controller midrange/low-end systems is obsolete.

 Customers now seek scale-out storage with low-latency NVMe SSDs for mission-critical block data and AI workloads requiring massive unstructured datasets. Disaggregated compute-storage architectures are gaining adoption for independent scaling of compute and storage. Disk-based systems are retained for nearline or warm data.

Selecting vendors and products for specific workload evaluations has grown more complex.

Magic Quadrant reports offer a detailed market positioning snapshot to identify viable vendors and serve as a starting point for IT procurement. Gartner’s companion Critical Capabilities report delivers deeper product evaluation for the same market segment, helping assess shortlisted vendors against RFP requirements. Organizations can use the Magic Quadrant to shortlist potential partners and Critical Capabilities to score products against their priority workload scenarios.

The 2026 Enterprise Storage Critical Capabilities assessment evaluated eight Magic Quadrant storage vendors across ten capabilities and seven use cases. Critical capabilities:

• --Performance and scalability
• --Resiliency and efficiency
• --Ecosystem
• --Hybrid IT operations management
• --Public cloud integration
• --Object storage
• --Cyber and data resilience
• --Virtualization and containers
• --Database integration
• --AI application integration

Seven use cases:

• --Online transaction processing (OLTP)
• --Virtualization and container management
• --High-performance file
• --Object-native applications
• --Hybrid platform services
• --Hybrid cloud storage
• --AI

Gartner analysts weight each critical capability and calculate vendor scores per use case. Huawei led three use cases — more than any other vendor: OLTP, High-Performance File, and AI application integration.

A radar chart visualizes the overall comparison. Gartner notes vendors are embedding cyber resilience, disaggregated scale-out designs and native AI data services across storage platforms. They are optimizing storage for high-performance file operations and demanding AI training/inference pipelines, while increasingly building native, hardware-accelerated or AI-powered ransomware detection directly into storage operating systems to speed threat identification.

Gartner states Huawei provides OceanStor Dorado for all-flash block and unified file storage, plus OceanStor Pacific for scale-out file, object and big data workloads. DME IQ, a centralized AIOps engine, delivers automated fault diagnosis, capacity forecasting and closed-loop lifecycle management across physical and hybrid cloud environments, orchestrating Huawei’s full storage portfolio globally.

Huawei earned its highest use-case scores for OLTP, high-performance file and AI, reflecting strengths in transactional database environments and large-scale unstructured data deployments increasingly used for AI inference.

Native shared-storage engine integration on the OceanStor block layer enables database instance recovery within seconds. OceanStor Dorado NAS also provides optimized NFS+ clients for database nodes to cut operational latency.

Data volumes for AI models and agent workloads may outpace all other storage workloads. AI transforms storage in three key ways: it requires ultra-fast access to massive unstructured data repositories; it enables machine-speed cyber-resilience to detect, block and recover from AI-fueled cyberattacks; and it simplifies storage monitoring and management while optimizing data placement.

Beijing Qianxing Jietong Technology Co., Ltd.
Sandy Yang/Global Strategy Director
WhatsApp / WeChat: +86 13426366826
Email: yangyd@qianxingdata.com
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