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市場調查報告書
商品編碼
1854151
雲端原生儲存市場按產品類型、部署模式、最終用戶產業、應用程式和組織規模分類 - 全球預測 2025-2032Cloud Native Storage Market by Product Type, Deployment Model, End User Industry, Application, Organization Size - Global Forecast 2025-2032 |
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預計到 2032 年,雲端原生儲存市場將成長至 1,273.4 億美元,複合年成長率為 24.65%。
| 關鍵市場統計數據 | |
|---|---|
| 基準年 2024 | 218.4億美元 |
| 預計年份:2025年 | 271.3億美元 |
| 預測年份 2032 | 1273.4億美元 |
| 複合年成長率 (%) | 24.65% |
雲端原生儲存已從一項實驗性技術轉變為企業尋求敏捷、彈性且經濟高效的資料管理的必要營運手段。隨著應用程式向容器化架構遷移,無狀態運算成為主流,持久性儲存也必須不斷發展,以滿足效能、可擴展性和維運簡易性方面的需求。本文將雲端原生儲存定位為策略賦能因素,它不僅是一種技術選擇,更能夠影響產品迭代速度、合規性和客戶體驗。
將儲存視為戰略能力的架構,將儲存設計融入應用架構、DevOps實踐和採購決策中。這種轉變促進了基礎設施、平台工程和應用團隊之間更緊密的協作,迫使資訊長 (CIO) 和首席技術長 (CTO) 重新思考供應商關係、授權模式和整體擁有成本。該架構的引入明確了互通性、資料移動性和自動化的預期,並揭示了儲存策略如何影響數位服務的上市時間。
最終,雲端原生儲存透過使平台團隊能夠交付可靠的、策略驅動的資訊服務,同時讓開發人員專注於功能開發,從而支援業務成果。將重點從單純採購硬體轉移到建立可組合的、軟體定義的儲存架構,並透過實際的試點專案和分階段部署檢驗,旨在降低風險並加速實現可衡量的價值。
雲端原生儲存領域正經歷多重變革,這些變革正在重塑企業設計和營運資訊服務的方式。首先,容器編配和平台工程的興起,推動了對動態配置、磁碟區生命週期管理以及跨分散式系統簡介一致性的需求。能夠與編配層無縫整合的儲存介面,可減少運維摩擦,縮短部署週期。
其次,微服務和多語言持久化的架構趨勢加劇了儲存需求的異質性,需要能夠支援高效能區塊I/O、可擴充物件儲存和分散式檔案語意的靈活解決方案。第三,開放原始碼創新和標準主導的介面正在擴展貢獻者和供應商的生態系統,為整合創造了新的機遇,同時也提高了嚴格測試和相容性檢驗的標準。這種開放的生態系統加速了創新,但也需要嚴格的管治來避免無序擴張。
第四,資料豐富性和監管方面的考量正在推動混合雲和多重雲端策略的發展,促使企業優先考慮可攜性、一致的管理平台和統一的資料保護策略。智慧遠端檢測和閉合迴路修復機制能夠縮短平均修復時間並最佳化資源利用率。這些轉變共同推動了那些提供 API 優先、模組化儲存服務的供應商和平台的發展,這些服務專為雲端原生環境設計,並能幫助平台團隊快速部署。
2025年關稅及貿易政策變化的實施對支撐雲端原生儲存基礎設施的全球供應鏈產生了累積影響。包括企業級儲存陣列、NVMe設備和專用加速器供應商在內的硬體依賴環節,由於關稅和合規措施已應用於各個組件層級,其到岸成本均有所增加。這些成本壓力已蔓延至採購環節,影響本地部署、託管和混合部署的經濟效益。
雲端服務供應商和軟體定義儲存供應商採取了不同的應對措施,一些供應商短期內自行承擔成本上漲以維持客戶支持,而另一些供應商則將與硬體和物流相關的價格調整轉嫁給客戶。因此,買家的行為轉向了更注重減少硬體依賴的解決方案,例如運行在通用伺服器上的純軟體儲存堆疊,以及利用公共雲端儲存層級,使供應商能夠大規模地最佳化全球供應和容量。為了抵消關稅的影響,採購團隊開始優先考慮營運總成本促進因素,例如能源效率、組件壽命和維護合約。
風險緩解策略也隨之演變。架構設計透過多元化供應商生態系統來降低集中關稅的影響,優先選擇擁有靈活生產佈局的供應商,並加速採用雲端優先架構,以將應用程式效能與區域硬體限制解耦。此外,更嚴格的庫存管理和更長期的供應商合約也成為應對投入成本波動的務實之舉。累積促成了雲端原生儲存決策的重新平衡,使其更加重視模組化、供應鏈彈性和營運模式,從而最大限度地減少對受關稅影響的硬體組件的依賴。
依產品類型分析雲端原生存儲,可以揭示其技術和營運方面的優先順序。區塊儲存用例需要低延遲、高吞吐量,並區分了支援事務性工作負載的直連儲存和 SAN 部署。文件儲存要求強調一致性和共用存取模式,常見於分散式檔案系統和傳統 NAS 部署,既支援傳統應用也支援現代應用。物件存儲,特別是與 S3 相容的架構,在需要大規模、具成本效益持久性和與雲端原生 API 整合的工作負載中佔據主導地位。
部署模型的分解揭示了控制與彈性之間的策略權衡。混合雲端雲和多重雲端方法優先考慮資料移動性、一致的策略執行以及跨本地和雲端資源的統一可觀測性。私有雲端環境通常是基於 Nutanix、OpenStack 和 VMware 生態系統客製化建構的平台,團隊需要在效能和管治之間取得平衡。公共雲端的選擇會影響營運整合和合作夥伴生態系統,阿里雲、亞馬遜雲端服務 (AWS)、谷歌雲端平台 (GCP) 和微軟 Azure 等主要供應商都提供原生儲存原語,但對第三方軟體堆疊的支援程度各不相同。
終端用戶產業對工作負載的具體需求各不相同:銀行、金融服務和保險業要求嚴格的資料保護、審核和低延遲交易處理;醫療保健產業優先考慮病患資料隱私、保留策略和互通性;IT和電訊需要高吞吐量、可擴展的儲存來支援網路功能和可觀測的管道;製造業重視工業控制系統的確定性性能;零售業專注於可擴展的資料湖和快速分析,以支援個人化和庫存最佳化;備份和復原解決方案強調持久性和快速恢復時間;巨量資料和分析需要容器化Terabyte擴展無元件功能;和策略驅動的編配展開。大型企業通常會投資於整合平台團隊和客製化實施方案,優先考慮合規性和可擴展性,而小型企業則傾向於選擇託管服務和簡化的營運模式,以加快價值實現速度。
在美洲,雲端原生儲存的普及主要得益於對開發者開發速度的重視、雲端遷移計畫的推進以及成熟的託管服務供應商生態系統。企業優先考慮與現有公共雲端平台的整合,並投資於可觀測性和自動化以支援規模化發展。法律規範強調資料保護和違規通知,促使企業加強加密、日誌記錄和不可篡改備份的投資,以滿足合規要求。
歐洲、中東和非洲的市場格局更為分散,監管環境、數據主權問題和基礎設施成熟度差異顯著。在許多歐洲、中東和非洲市場,企業需要在公有雲的優勢與嚴格的在地化要求和行業特定法規之間尋求平衡。這種動態推動了對混合架構、主權雲和私有雲端部署的需求,這些方案既能滿足合規性要求,又能提供現代化的資訊服務。商業模式通常圍繞著與本地系統整合和雲端服務供應商夥伴關係展開,以獲得在地化支援。
亞太地區正呈現快速成長和多元化的雲端應用模式,這主要得益於大量的雲端投資、行動優先的消費行為以及強勁的製造業和通訊業。該地區擁有成熟的雲端市場和快速數位化的經濟體,部署方式也多種多樣,從完全公有雲部署到在地化的私有平台,應有盡有。能夠提供靈活的消費模式、支援多種語言和法規環境以及擁有強大的區域合作夥伴網路的雲端服務供應商,預計將在亞太地區蓬勃發展。
雲端原生儲存供應商生態系統涵蓋了現有基礎設施供應商、雲端服務供應商以及開放原始碼主導的參與企業。成功要素包括清晰的 Kubernetes 原生整合藍圖、強大的資料保護和複製能力,以及對標準化和互通性的承諾。那些將強大的合作夥伴計劃與承包託管方案相結合的供應商,通常能夠加速缺乏深厚內部平台專業知識的企業採用雲端原生儲存解決方案。
軟體供應商與公共雲端供應商之間的策略夥伴關係拓展了解決方案範圍並簡化了採購流程,而開放原始碼社群則推動了功能快速迭代和更廣泛的貢獻者群體。商業模式涵蓋了從訂閱式軟體到按需付費的託管服務,供應商透過提供支援保證、認證計劃和專業服務來簡化遷移流程,從而實現差異化競爭。在複雜的企業環境中,能夠幫助系統整合商和託管服務供應商將儲存服務整合到更廣泛的平台產品中的通路策略尤為有效。
影響買方決策的營運差異化因素包括遙測資料的準確性、與基礎設施即代碼 (IaC) 工具的整合,以及災難恢復和跨區域複製能力的成熟度。投資於自動化檢驗、清晰的操作手冊和廣泛的互通性測試的供應商,能夠減少平台團隊的阻力,並縮短開發團隊的運作部署時間。最後,透明的定價和可預測的營運成本,在採購團隊比較不同方案時,能夠增強供應商的價值提案。
首先,要使儲存策略與應用程式優先權保持一致。進行能力映射,將儲存特性與關鍵工作負載和復原目標關聯起來。這種匹配將明確工作負載是否需要低延遲塊性能、共用文件語義或大規模可擴展的對象存儲,從而突出整合冗餘存儲孤島的機會。接下來,優先考慮自動化和 API主導的操作,投資於平台工程能力,將配置、策略執行和遙測資料收集編碼化。這項投資將降低維運開銷,並減少動態環境中的人為錯誤。
實現供應商關係多元化,並採用軟體優先策略,以降低組件主導的成本衝擊。透過檢驗S3 相容性、CSI 驅動程式支援以及對開放標準的遵循情況,將互通性和可移植性納入選擇標準。透過將資料生命週期策略納入基礎設施即程式碼,並在存在監管要求的情況下強制執行加密和不可變性,來加強管治。最後,透過針對性的培訓、運作手冊編寫和跨職能演練,投資提昇平台和維運團隊的技能,進而提高生產部署的可靠性。採用這些做法將加速部署,同時降低風險並帶來可衡量的營運效益。
本研究採用混合方法,結合一手資料和二手資料,以確保全面涵蓋和平衡觀點。一手資料包括對基礎設施、平台工程和採購領域的從業人員進行結構化訪談,以及與供應商產品和策略負責人進行討論,以了解他們的產品藍圖和商業模式。這些訪談為採用模式、營運挑戰和決策標準提供了背景資訊,從而為策略建議提供依據。
二次研究包括查閱技術文件、供應商白皮書、產品發布說明和官方監管指南,以驗證訪談結果並檢驗技術論點。數據綜合採用主題分析法分析質性數據,並在條件允許的情況下,利用多個獨立資訊來源交叉檢驗說明。調查方法強調可重複性,詳細記錄了訪談通訊協定、供應商和案例研究的選擇標準以及得出建議的邏輯。研究的局限性在於技術和政策的不斷演變;調查方法考慮到了這一點,優先考慮反覆驗證的資訊,而非單一來源的軼事。
雲端原生儲存是企業追求現代化應用架構和更快產品週期的關鍵策略組成部分。它需要一種整合的方法,將技術評估、採購規範和組織變革管理結合。那些將儲存視為平台服務並投資於自動化、互通性和供應商多元化的領導者,最能充分利用現代資料架構帶來的營運和業務優勢。
未來,成功的企業將採用模組化、API優先的儲存平台,透過實際試點檢驗互通性,並將管治和遠端檢測融入日常營運。遵循本文提出的基於實證的實踐和建議,企業主管和技術領導者可以降低部署風險,最佳化營運成本,並解鎖分析、彈性和開發人員生產力的新功能。
The Cloud Native Storage Market is projected to grow by USD 127.34 billion at a CAGR of 24.65% by 2032.
| KEY MARKET STATISTICS | |
|---|---|
| Base Year [2024] | USD 21.84 billion |
| Estimated Year [2025] | USD 27.13 billion |
| Forecast Year [2032] | USD 127.34 billion |
| CAGR (%) | 24.65% |
Cloud native storage has transitioned from an experimental technology to an operational imperative for organizations seeking agility, resilience, and cost-effective data management. As applications shift to containerized architectures and stateless compute becomes the norm, persistent storage must evolve to meet requirements for performance, scalability, and operational simplicity. This introduction frames cloud native storage not merely as a technical choice but as a strategic enabler that impacts product velocity, regulatory compliance, and customer experience.
Organizations that treat storage as a strategic capability integrate storage design into application architecture, DevOps practices, and procurement decisions. This shift encourages closer collaboration between infrastructure, platform engineering, and application teams, and it compels CIOs and CTOs to rethink vendor relationships, licensing models, and total cost of ownership considerations. The introduction sets expectations around interoperability, data mobility, and automation, and highlights how storage strategy influences time-to-market for digital services.
Ultimately, cloud native storage supports business outcomes by enabling developers to focus on features while platform teams deliver reliable, policy-driven data services. The emphasis moves from isolated hardware procurement toward building composable, software-defined storage fabrics that are validated through pragmatic pilot programs and phased rollouts designed to reduce risk and accelerate measurable value.
The cloud native storage landscape is experiencing multiple concurrent shifts that are transforming how organizations design and operate data services. First, the rise of container orchestration and platform engineering has elevated requirements for dynamic provisioning, volume life-cycle management, and snapshot consistency across distributed systems. Storage interfaces that integrate seamlessly with orchestration layers reduce operational friction and shorten deployment cycles.
Second, architectural trends toward microservices and polyglot persistence are increasing the heterogeneity of storage needs, requiring flexible solutions that support high-performance block I/O, scalable object stores, and distributed file semantics. Third, open-source innovations and standards-driven interfaces have expanded the ecosystem of contributors and vendors, creating new opportunities for integration while also raising the bar for rigorous testing and compatibility validation. This open ecosystem accelerates innovation but requires disciplined governance to avoid sprawl.
Fourth, data gravity and regulatory considerations are driving hybrid and multi-cloud strategies, prompting organizations to prioritize portability, consistent management planes, and unified data protection policies. Finally, automation and AI-driven operations are becoming standard expectations; intelligent telemetry and closed-loop remediation reduce mean time to repair and optimize resource utilization. Collectively, these shifts favor vendors and platforms that deliver modular, API-first storage services designed for cloud native environments and for rapid operationalization by platform teams.
The imposition of tariffs and trade policy changes in 2025 has had a cumulative effect on global supply chains that support cloud native storage infrastructure. Hardware-dependent segments, including suppliers of enterprise storage arrays, NVMe devices, and specialized accelerators, experienced increased landed costs as duties and compliance measures were applied across component tiers. These cost pressures have reverberated through procurement cycles and influenced the economics of on-premises, co-located, and hybrid deployments.
Cloud service providers and software-defined storage vendors responded in multiple ways: some absorbed incremental costs in the short term to maintain customer traction, while others passed through price adjustments tied to hardware and logistics. As a result, buyer behavior shifted toward solutions that emphasize lower hardware dependency, such as software-only storage stacks that run on commodity servers, and toward leveraging public cloud storage tiers where providers could optimize global supply and capacity at scale. Procurement teams increased emphasis on total operational cost drivers, including power efficiency, component longevity, and maintenance contracts, to offset tariff impacts.
Risk mitigation strategies also evolved. Organizations diversified supplier ecosystems to reduce exposure to concentrated tariffs, prioritized vendors with flexible manufacturing footprints, and accelerated adoption of cloud-first architectures to decouple application performance from localized hardware constraints. Additionally, tighter inventory management and longer-term supplier agreements emerged as practical responses to input cost volatility. The cumulative effect has been a rebalancing of cloud native storage decisions toward modularity, supply chain resilience, and operational models that minimize dependency on tariff-exposed hardware components.
Analyzing cloud native storage through product type reveals distinct technical and operational priorities. Block storage use cases demand low-latency, high-throughput characteristics and are differentiated between Direct Attached Storage and SAN deployments that underpin transactional workloads. File storage requirements emphasize consistency and shared access patterns, seen across Distributed File Systems and traditional NAS deployments that support legacy and modern applications alike. Object storage, particularly S3-compatible architectures, dominates workloads requiring massive scale, cost-effective durability, and integration with cloud-native APIs.
Deployment model segmentation exposes strategic trade-offs between control and elasticity. Hybrid cloud and multi-cloud approaches prioritize data mobility, consistent policy enforcement, and unified observability across on-premises and cloud resources. Private cloud environments often represent bespoke platforms implemented on Nutanix, OpenStack, or VMware ecosystems where teams balance performance and governance. Public cloud choices influence operational integration and partner ecosystems, with major providers such as Alibaba Cloud, Amazon Web Services, Google Cloud Platform, and Microsoft Azure each offering native storage primitives and varying support for third-party software stacks.
End-user industries drive workload-specific expectations. Banking, financial services and insurance demand stringent data protection, auditability, and low-latency transaction processing; healthcare prioritizes patient data privacy, retention policies, and interoperability; IT and telecom require high-throughput, scalable storage to support network functions and observability pipelines; manufacturing emphasizes deterministic performance for industrial control systems; and retail focuses on scalable data lakes and rapid analytics to support personalization and inventory optimization. Application segmentation further clarifies investments: backup and recovery solutions emphasize durability and fast restore times, big data and analytics demand scalable object and distributed file capabilities, containerized environments require dynamic provisioning and ephemeral volume strategies, data archiving focuses on cost per terabyte and long-term integrity, and DevOps automation centers on programmable storage APIs and policy-driven orchestration. Organization size shapes adoption cadence and governance: large enterprises typically invest in integrated platform teams and bespoke deployments that prioritize compliance and scale, while small and medium enterprises tend to favor managed services and simplified operational models that accelerate time to value.
In the Americas, adoption of cloud native storage is driven by a strong emphasis on developer velocity, cloud migration initiatives, and a mature ecosystem of managed service providers. Organizations prioritize integration with established public cloud platforms and invest in observability and automation to support scale. Regulatory frameworks emphasize data protection and breach notification, prompting investments in encryption, logging, and immutable backups to meet compliance obligations.
Europe, the Middle East and Africa present a more fragmented landscape where regulatory regimes, data sovereignty concerns, and infrastructure maturity vary considerably. In many EMEA markets, organizations balance the benefits of public cloud with stringent localization requirements and sector-specific regulations. This dynamic fuels demand for hybrid architectures, sovereign cloud offerings, and private cloud deployments that can deliver both compliance and modern data services. Commercial models often center on partnerships with regional system integrators and cloud providers that offer localized support.
Asia-Pacific demonstrates rapid growth and diverse adoption patterns driven by large-scale cloud investment, mobile-first consumer behavior, and a robust manufacturing and telecom sector. The region includes mature cloud markets alongside rapidly digitizing economies, leading to a broad spectrum of deployment approaches from full public cloud adoption to localized private platforms. Providers that offer flexible consumption models, support for multiple language and regulatory environments, and strong regional partner networks tend to gain traction in Asia-Pacific.
The cloud native storage vendor ecosystem reflects a blend of established infrastructure vendors, cloud service providers, and open-source-driven entrants. Success factors include a clear roadmap for Kubernetes-native integration, robust data protection and replication capabilities, and a commitment to standards and interoperability. Vendors that combine strong partner programs with turnkey managed options often accelerate adoption among enterprises that lack deep in-house platform expertise.
Strategic partnerships between software vendors and public cloud providers extend solution reach and simplify procurement, while open-source communities drive rapid feature cycles and broaden contributor bases. Commercial models vary from subscription-based software to consumption-based managed services, and vendors differentiate through support guarantees, certification programs, and professional services that ease migration. Channel strategies that enable system integrators and managed service providers to embed storage services into broader platform offerings are particularly effective in complex enterprise environments.
Operational differentiators that influence buyer decisions include telemetry fidelity, integration with infrastructure-as-code tooling, and the maturity of disaster recovery and cross-region replication features. Vendors that invest in automated validation, clear operational runbooks, and extensive interoperability testing reduce friction for platform teams and improve time to production for developer teams. Finally, transparent pricing mechanics and predictable operational costs strengthen vendor value propositions when procurement teams compare alternatives.
Begin by aligning storage strategy with application priorities; conduct a capability mapping exercise that links storage characteristics to critical workloads and recovery objectives. This alignment clarifies whether workloads need low-latency block performance, shared file semantics, or massively scalable object storage, and it surfaces opportunities to consolidate redundant storage silos. Next, prioritize automation and API-driven operations by investing in platform engineering capabilities that codify provisioning, policy enforcement, and telemetry collection. This investment lowers operational overhead and reduces human error in dynamic environments.
Diversify supplier relationships and favor software-first approaches to reduce exposure to component-driven cost shocks. Incorporate interoperability and portability as selection criteria by validating S3 compatibility, CSI driver support, and adherence to open standards. Strengthen governance by embedding data lifecycle policies into infrastructure-as-code and by enforcing encryption and immutability where regulatory obligations demand it. Finally, invest in upskilling platform and operations teams through targeted training, runbook development, and cross-functional exercises that build confidence for production rollouts. Adopting these practices will accelerate adoption while lowering risk and delivering measurable operational benefits.
This research employed a mixed-methods approach combining primary and secondary inputs designed to ensure comprehensive coverage and balanced perspective. Primary research included structured interviews with practitioners across infrastructure, platform engineering, and procurement functions, alongside discussions with vendor product and strategy leaders to understand roadmaps and commercial models. These interviews provided context on deployment patterns, operational challenges, and decision criteria that inform strategic recommendations.
Secondary research examined technical documentation, vendor white papers, product release notes, and public regulatory guidance to triangulate findings from interviews and to validate technical assertions. Data synthesis applied thematic analysis to qualitative inputs and cross-validated statements using multiple independent sources where available. The methodology emphasized reproducibility by documenting interview protocols, inclusion criteria for vendor and case study selection, and the logic used to derive recommendations. Limitations include the evolving nature of technology and policy, which the methodology accounts for by prioritizing recurring, corroborated signals over single-source anecdotes.
Cloud native storage is a strategic linchpin for organizations pursuing modern application architectures and accelerated product cycles. It demands an integrated approach that combines technical evaluation, procurement discipline, and organizational change management. Leaders who treat storage as a platform service and invest in automation, interoperability, and supplier diversity will be better positioned to capture the operational and business benefits of modern data architectures.
Looking forward, success will favor organizations that adopt modular, API-first storage platforms, that validate interoperability through practical pilots, and that embed governance and telemetry into everyday operations. By following the evidence-based practices and recommendations presented here, executives and technical leaders can reduce deployment risk, optimize operational costs, and unlock new capabilities for analytics, resilience, and developer productivity.