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市场调查报告书
商品编码
1854151
云端原生储存市场按产品类型、部署模式、最终用户产业、应用程式和组织规模划分 - 全球预测 2025-2032Cloud Native Storage Market by Product Type, Deployment Model, End User Industry, Application, Organization Size - Global Forecast 2025-2032 |
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预计到 2032 年,云端原生储存市场将成长至 1,273.4 亿美元,复合年增长率为 24.65%。
| 关键市场统计数据 | |
|---|---|
| 基准年 2024 | 218.4亿美元 |
| 预计年份:2025年 | 271.3亿美元 |
| 预测年份 2032 | 1273.4亿美元 |
| 复合年增长率 (%) | 24.65% |
云端原生储存已从一项实验性技术转变为企业寻求敏捷、弹性且经济高效的资料管理的必要营运手段。随着应用程式向容器化架构迁移,无状态运算成为主流,持久性储存也必须不断发展,以满足效能、可扩展性和维运简易性方面的需求。本文将云端原生储存定位为策略赋能因素,它不仅是一种技术选择,更能够影响产品迭代速度、合规性和客户体验。
将储存视为战略能力的架构,将储存设计融入应用架构、DevOps实践和采购决策中。这种转变促进了基础设施、平台工程和应用团队之间更紧密的协作,迫使资讯长 (CIO) 和首席技术长 (CTO) 重新思考供应商关係、授权模式和整体拥有成本。该架构的引入明确了互通性、资料移动性和自动化的预期,并揭示了储存策略如何影响数位服务的上市时间。
最终,云端原生储存透过使平台团队能够交付可靠的、策略驱动的资讯服务,同时让开发人员专注于功能开发,从而支援业务成果。将重点从单纯采购硬体转移到建立可组合的、软体定义的储存架构,并透过实际的试点专案和分阶段部署检验,旨在降低风险并加速实现可衡量的价值。
云端原生储存领域正经历多重变革,这些变革正在重塑企业设计和营运资讯服务的方式。首先,容器编配和平台工程的兴起,推动了对动态配置、磁碟区生命週期管理以及跨分散式系统简介一致性的需求。能够与编配层无缝整合的储存接口,可减少运维摩擦,缩短部署週期。
其次,微服务和多语言持久化的架构趋势加剧了储存需求的异质性,需要能够支援高效能区块I/O、可扩充物件储存和分散式檔案语意的灵活解决方案。第三,开放原始码创新和标准主导的介面正在扩展贡献者和供应商的生态系统,为整合创造了新的机会,同时也提高了严格测试和相容性检验的标准。这种开放的生态系统加速了创新,但也需要严格的管治来避免无序扩张。
第四,资料丰富性和监管方面的考量正在推动混合云和多重云端策略的发展,促使企业优先考虑可携性、一致的管理平台和统一的资料保护策略。智慧远端检测和闭合迴路修復机制能够缩短平均修復时间并优化资源利用率。这些转变共同推动了那些提供 API 优先、模组化储存服务的供应商和平台的发展,这些服务专为云端原生环境设计,并能帮助平台团队快速部署。
2025年关税及贸易政策变化的实施对支撑云端原生储存基础设施的全球供应链产生了累积影响。包括企业级储存阵列、NVMe设备和专用加速器供应商在内的硬体依赖环节,由于关税和合规措施已应用于各个组件层级,其到岸成本均有所增加。这些成本压力已蔓延至采购环节,影响本地部署、託管和混合部署的经济效益。
云端服务供应商和软体定义储存供应商采取了不同的应对措施,一些供应商短期内自行承担成本上涨以维持客户支持,而另一些供应商则将与硬体和物流相关的价格调整转嫁给客户。因此,买家的行为转向了更注重减少硬体依赖的解决方案,例如运行在通用伺服器上的纯软体储存堆迭,以及利用公共云端储存层级,使供应商能够大规模地优化全球供应和容量。为了抵消关税的影响,采购团队开始优先考虑营运总成本驱动因素,例如能源效率、组件寿命和维护合约。
风险缓解策略也随之演变。架构设计透过多元化供应商生态系统来降低集中关税的影响,优先选择拥有灵活生产布局的供应商,并加速采用云端优先架构,以将应用程式效能与区域硬体限制解耦。此外,更严格的库存管理和更长期的供应商合约也成为应对投入成本波动的务实之举。累积促成了云端原生储存决策的重新平衡,使其更加重视模组化、供应链弹性和营运模式,从而最大限度地减少对受关税影响的硬体组件的依赖。
依产品类型分析云端原生存储,可以揭示其技术和营运方面的优先顺序。区块储存用例需要低延迟、高吞吐量,并区分了支援事务性工作负载的直连储存和 SAN 部署。文件储存要求强调一致性和共用存取模式,常见于分散式檔案系统和传统 NAS 部署,既支援传统应用也支援现代应用。物件存储,特别是与 S3 相容的架构,在需要大规模、高性价比持久性和与云端原生 API 整合的工作负载中占据主导地位。
部署模型的分解揭示了控制与弹性之间的策略权衡。混合云端云和多重云端方法优先考虑资料移动性、一致的策略执行以及跨本地和云端资源的统一可观测性。私有云端环境通常是基于 Nutanix、OpenStack 和 VMware 生态系统客製化建构的平台,团队需要在效能和管治之间取得平衡。公共云端的选择会影响营运整合和合作伙伴生态系统,阿里云、亚马逊云端服务 (AWS)、谷歌云端平台 (GCP) 和微软 Azure 等主要供应商都提供原生储存原语,但对第三方软体堆迭的支援程度各不相同。
终端用户产业对工作负载的具体需求各不相同:银行、金融服务和保险业要求严格的资料保护、审核和低延迟交易处理;医疗保健产业优先考虑病患资料隐私、保留策略和互通性;IT和电讯需要高吞吐量、可扩展的储存来支援网路功能和可观测的管道;製造业重视工业控制系统的确定性性能;零售业专注于可扩展的资料湖和快速分析,以支援个人化和库存最佳化;备份和復原解决方案强调持久性和快速恢復时间;巨量资料和分析需要容器化Terabyte扩展无元件功能;和策略驱动的编配展开。大型企业通常会投资于整合平台团队和客製化实施方案,优先考虑合规性和可扩展性,而小型企业则倾向于选择託管服务和简化的营运模式,以加快价值实现速度。
在美洲,云端原生储存的普及主要得益于对开发者开发速度的重视、云端迁移计画的推进以及成熟的託管服务供应商生态系统。企业优先考虑与现有公共云端平台的集成,并投资于可观测性和自动化以支援规模化发展。法律规范强调资料保护和违规通知,促使企业加强加密、日誌记录和不可篡改备份的投资,以满足合规要求。
欧洲、中东和非洲的市场格局更为分散,监管环境、数据主权问题和基础设施成熟度差异显着。在许多欧洲、中东和非洲市场,企业需要在公有云的优势与严格的在地化要求和行业特定法规之间寻求平衡。这种动态推动了对混合架构、主权云和私有云端部署的需求,这些方案既能满足合规性要求,又能提供现代化的资讯服务。商业模式通常围绕着与本地系统整合和云端服务供应商伙伴关係展开,以获得在地化支援。
亚太地区正呈现快速成长和多元化的云端应用模式,这主要得益于大量的云端投资、行动优先的消费行为以及强劲的製造业和通讯业。该地区拥有成熟的云端市场和快速数位化的经济体,部署方式也多种多样,从完全公有云部署到在地化的私有平台,应有尽有。能够提供灵活的消费模式、支援多种语言和法规环境以及拥有强大的区域合作伙伴网路的云端服务供应商,预计将在亚太地区蓬勃发展。
云端原生储存供应商生态系统涵盖了现有基础设施供应商、云端服务供应商以及开放原始码主导的参与企业。成功要素包括清晰的 Kubernetes 原生整合蓝图、强大的资料保护和复製能力,以及对标准化和互通性的承诺。那些将强大的合作伙伴计划与承包託管方案相结合的供应商,通常能够加速缺乏深厚内部平台专业知识的企业采用云端原生储存解决方案。
软体供应商与公共云端供应商之间的策略伙伴关係拓展了解决方案范围并简化了采购流程,而开放原始码社群则推动了功能快速迭代和更广泛的贡献者群体。商业模式涵盖了从订阅式软体到按需付费的託管服务,供应商透过提供支援保证、认证计划和专业服务来简化迁移流程,从而实现差异化竞争。在复杂的企业环境中,能够帮助系统整合商和託管服务供应商将储存服务整合到更广泛的平台产品中的通路策略尤为有效。
影响买方决策的营运差异化因素包括遥测资料的准确性、与基础设施即代码 (IaC) 工具的集成,以及灾难恢復和跨区域复製能力的成熟度。投资于自动化检验、清晰的操作手册和广泛的互通性测试的供应商,能够减少平台团队的阻力,并缩短开发团队的运作部署时间。最后,透明的定价和可预测的营运成本,在采购团队比较不同方案时,能够增强供应商的价值提案。
首先,要使储存策略与应用程式优先权保持一致。进行能力映射,将储存特性与关键工作负载和復原目标关联起来。这种匹配将明确工作负载是否需要低延迟块性能、共用文件语义或大规模可扩展的对象存储,从而突出整合冗余存储孤岛的机会。接下来,优先考虑自动化和 API主导的操作,投资于平台工程能力,将配置、策略执行和遥测资料收集编码化。这项投资将降低维运开销,并减少动态环境中的人为错误。
实现供应商关係多元化,并采用软体优先策略,以降低组件主导的成本衝击。透过检验S3 相容性、CSI 驱动程式支援以及对开放标准的遵循情况,将互通性和可移植性纳入选择标准。透过将资料生命週期策略纳入基础设施即程式码,并在存在监管要求的情况下强制执行加密和不可变性,来加强管治。最后,透过针对性的培训、运作手册编写和跨职能演练,投资提昇平台和维运团队的技能,进而提高生产部署的可靠性。采用这些做法将加速部署,同时降低风险并带来可衡量的营运效益。
本研究采用混合方法,结合一手资料和二手资料,以确保全面涵盖和平衡观点。一手资料包括对基础设施、平台工程和采购领域的从业人员进行结构化访谈,以及与供应商产品和策略负责人进行讨论,以了解他们的产品蓝图和商业模式。这些访谈为采用模式、营运挑战和决策标准提供了背景信息,从而为策略建议提供依据。
二次研究包括查阅技术文件、供应商白皮书、产品发布说明和官方监管指南,以验证访谈结果并检验技术论点。数据综合采用主题分析法分析质性数据,并在条件允许的情况下,利用多个独立资讯来源交叉检验说明。调查方法强调可重复性,详细记录了访谈通讯协定、供应商和案例研究的选择标准以及得出建议的逻辑。研究的局限性在于技术和政策的不断演变;调查方法考虑到了这一点,优先考虑反覆验证的信息,而非单一来源的轶事。
云端原生储存是企业追求现代化应用架构和更快产品週期的关键策略组成部分。它需要一种整合的方法,将技术评估、采购规范和组织变革管理结合。那些将储存视为平台服务并投资于自动化、互通性和供应商多元化的领导者,最能充分利用现代资料架构带来的营运和业务优势。
未来,成功的企业将采用模组化、API优先的储存平台,透过实际试点检验互通性,并将管治和远端检测融入日常营运。遵循本文提出的基于实证的实践和建议,企业主管和技术领导者可以降低部署风险,优化营运成本,并解锁分析、弹性和开发人员生产力的新功能。
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.