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市场调查报告书
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1918496

资料灾害復原市场按组件、部署模式、组织规模和最终用户产业划分 - 全球预测 2026-2032 年

Data Disaster Recovery Market by Component (Services, Solutions), Deployment Model (Cloud, Hybrid, On Premises), Organization Size, End User Industry - Global Forecast 2026-2032
出版日期: | 出版商: 360iResearch | 英文 184 Pages | 商品交期: 最快1-2个工作天内

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预计到 2025 年，资料灾害復原市场规模将达到 1.9,247 亿美元，到 2026 年将成长至 2.1117 亿美元，到 2032 年将达到 3.4863 亿美元，复合年增长率为 8.85%。

关键市场统计数据
基准年 2025 1.9247亿美元
预计年份：2026年 2.1117亿美元
预测年份 2032 3.4863亿美元
复合年增长率 (%) 8.85%

本文简要概述了现代资料连续性面临的挑战、管治的改变，以及为何復原策略现在需要跨职能的业务协作。

现代企业面临的资料连续性环境比过去几十年复杂得多。分散式云端原生应用、广泛的远端办公以及关键任务资料在混合基础设施上的日益增多，都扩大了攻击面，也增加了发生事件时必须维护的业务依赖性。因此，资料灾害復原已从单一的技术学科发展成为一项跨职能的业务能力，与收入连续性、合规性和客户信任息息相关。

云端转型、网路威胁趋势、自动化和监管限制正在重塑恢復架构和策略供应商伙伴关係。

资料灾害復原格局正沿着多个变革轴发生转变，重新定义企业建构韧性的方式。首先，云端原生和容器化工作负载使得復原计画更加分散和去中心化。復原不再仅依赖资料中心容错移转，而是围绕着跨多个环境的应用层级编配。同时，勒索软体和其他定向勒索手段的兴起迫使团队在增强检测和遏制能力的同时，优先考虑快速及时的恢復路径。

近期关税调整对采购、供应链韧性以及本地部署和云端恢復方案之间的策略选择所产生的实际影响

2025 年的关税调整和贸易政策更新为那些资料保护生态系统依赖跨境供应链和跨国供应商关係的组织带来了新的营运考量。硬体组件和储存设备关税的变化将影响本地恢復基础设施的采购计划和整体拥有成本，而进口法规的波动则可能对关键替换零件的供应商交货时间产生影响。

有针对性的细分洞察，解释了组件选择、部署模式、组织规模和行业细分将如何重塑復苏优先事项和投资。

有效的细分观点能够明确弹性投资在哪些方面能够带来最大的业务价值，并帮助领导者确定架构和服务选择的优先顺序。市场调查根据组件将“服务”和“解决方案”区分开来。 「服务」维度区分了不同的交付类型，例如咨询/支援和託管服务，这些服务满足管治、测试和外包编配需求。 「解决方案」维度进一步细分为云端、混合和本地部署三种方式，反映了敏捷性、控制和资料本地性之间不同的营运权衡。

区域管理体制、基础设施可用性和供应商生态系统如何导致全球市场差异化的復苏需求

区域趋势对组织如何规划和实施资料灾害復原有显着影响。地理风险因素的认知体现在架构决策和供应商选择两个面向。在美洲，监管成熟度和企业IT基础设施规模往往促使企业儘早采用进阶编配工具和多重云端容错移转配置。同时，由于供应链限制，采购的考量仍然是本地部署的关键因素。

在现代恢復方案中，供应商和伙伴关係的趋势是优先考虑编配、云端原生整合和基于结果的託管服务。

资料灾害復原领域的供应商发展趋势日益侧重于编配能力、云端原生整合和透明的服务承诺。领先的解决方案供应商正在投资自动化层，以抽象化复杂的復原工作流程，并将检测、遏制和復原流程整合到统一的剧本中。同时，服务供应商正透过以结果为导向的合约和扩展的託管服务产品来实现差异化，这些产品融合了咨询、测试和实际操作。

领导企业现在应该采取哪些具体的管治、自动化、供应商多元化和检验措施，以大幅提高灾后復原准备能力？

领导者可以采取多项切实可行的措施来增强韧性，确保復原计画在不断变化的威胁和监管要求下保持有效。首先，将復原目标和测试节奏纳入企业风险管治，确保业务负责人明确恢復时间和资料关键性的优先级，并确保桌面演练和即时復原演练都得到规划和记录。这个管治步骤有助于提升课责，并揭示应用团队和基础架构团队之间隐藏的依赖关係。

结合从业者访谈、第二手资料分析和情境检验的混合调查方法，确保了研究结果的实用性和实证性。

研究结果以严谨的调查方法为支撑，该方法结合了结构化的初步研究以及对二级资讯来源的整合与检验。一级资讯来源包括对高级IT、安全和业务永续营运负责人的访谈；与基础设施和服务供应商的面对面交流；以及基于情境的案头研究，旨在揭示在真实事件模拟过程中决策的权衡取舍。这些负责人揭示了营运实务、采购考量和供应商绩效考量，为提出切实可行的建议奠定了基础。

一项综合分析，将现代恢復定位为一项策略性和可衡量的学科，它将自动化、管治和供应商韧性与业务永续营运成果联繫起来。

云端运算普及率不断提高、网路威胁日益增长、资费波动以及法规结构日益严格等因素的综合影响，已使资料灾害復原从单纯的营运保障转变为一项战略能力。那些将资料復原视为一项持续、可衡量的机制，并整合自动化、持续检验和跨职能管治的企业，能够透过减少停机时间、维护客户信任和简化合规流程，创造可持续的竞争优势。

目录

第一章：序言

第二章调查方法

  • 研究设计
  • 研究框架
  • 市场规模预测
  • 数据三角测量
  • 调查结果
  • 调查前提
  • 调查限制

第三章执行摘要

  • 首席体验长观点
  • 市场规模和成长趋势
  • 2025年市占率分析
  • FPNV定位矩阵，2025
  • 新的商机
  • 下一代经营模式
  • 产业蓝图

第四章 市场概览

  • 产业生态系与价值链分析
  • 波特五力分析
  • PESTEL 分析
  • 市场展望
  • 上市策略

第五章 市场洞察

  • 消费者洞察与终端用户观点
  • 消费者体验基准
  • 机会地图
  • 分销通路分析
  • 价格趋势分析
  • 监理合规和标准框架
  • ESG与永续性分析
  • 中断和风险情景
  • 投资报酬率和成本效益分析

第六章：美国关税的累积影响，2025年

第七章：人工智慧的累积影响，2025年

8. 资料灾害復原市场（依组件划分）

  • 服务
    • 咨询与支持
    • 託管服务
  • 解决方案
    • 基于云端的
    • 杂交种
    • 本地部署

9. 依部署模式分類的资料灾害復原市场

  • 云
  • 杂交种
  • 本地部署

第十章：依组织规模分類的资料灾害復原市场

  • 大公司
  • 小型企业

第十一章：以最终用户产业分類的资料灾害復原市场

  • BFSI
  • 政府
  • 卫生保健
  • 资讯科技/通讯
  • 零售

第十二章：按地区分類的资料灾害復原市场

  • 美洲
    • 北美洲
    • 拉丁美洲
  • 欧洲、中东和非洲
    • 欧洲
    • 中东
    • 非洲
  • 亚太地区

第十三章：按组别分類的资料灾害復原市场

  • ASEAN
  • GCC
  • EU
  • BRICS
  • G7
  • NATO

第十四章：各国资料灾害復原市场

  • 美国
  • 加拿大
  • 墨西哥
  • 巴西
  • 英国
  • 德国
  • 法国
  • 俄罗斯
  • 义大利
  • 西班牙
  • 中国
  • 印度
  • 日本
  • 澳洲
  • 韩国

第十五章美国资料灾害復原市场

第十六章：中国资料灾害復原市场

第十七章 竞争格局

  • 市场集中度分析，2025年
    • 浓度比（CR）
    • 赫芬达尔-赫希曼指数 (HHI)
  • 近期趋势及影响分析，2025 年
  • 2025年产品系列分析
  • 基准分析，2025 年
  • Acronis International GmbH
  • Amazon Web Services, Inc.
  • Broadcom Inc.
  • Capgemini SE
  • Cisco Systems, Inc.
  • Cohesity, Inc.
  • Commvault Systems, Inc.
  • Dell Technologies Inc.
  • Fujitsu Limited
  • Hewlett Packard Enterprise Company
  • Hitachi Vantara LLC
  • Infosys Limited
  • International Business Machines Corporation
  • Iron Mountain Incorporated
  • Microsoft Corporation
  • NetApp, Inc.
  • NTT DATA Group Corporation
  • Oracle Corporation
  • Rubrik, Inc.
  • Tata Consultancy Services Limited
  • Veeam Software AG
  • Veritas Technologies LLC
  • Wipro Limited
  • Zerto Ltd.
Product Code: MRR-AE420CB1558F

The Data Disaster Recovery Market was valued at USD 192.47 million in 2025 and is projected to grow to USD 211.17 million in 2026, with a CAGR of 8.85%, reaching USD 348.63 million by 2032.

KEY MARKET STATISTICS
Base Year [2025] USD 192.47 million
Estimated Year [2026] USD 211.17 million
Forecast Year [2032] USD 348.63 million
CAGR (%) 8.85%

A concise overview of modern data continuity pressures, governance shifts, and why recovery strategy now demands cross-functional business alignment

Organizations today confront a vastly more complex data continuity environment than in prior decades. Dispersed cloud-native applications, remote workforce patterns, and the proliferation of mission-critical data across hybrid infrastructures have expanded both the attack surface and the operational dependencies that must be preserved during incidents. As a result, data disaster recovery has evolved from a narrowly technical discipline into a cross-functional business capability that ties directly to revenue continuity, regulatory compliance, and customer trust.

Transitioning from legacy backup routines to modern recovery architectures requires not only new tools but also clarified governance, updated service level objectives, and collaboration between IT, security, legal, and business units. The move to cloud-based solutions and services simplifies certain operational burdens while introducing questions about recovery orchestration, vendor lock-in, and shared responsibility models. Consequently, leaders must reconcile technical feasibility with contract terms and data locality constraints.

This introduction outlines the operating realities driving current investment and strategy debates. It underscores why recovery objectives, threat preparedness, and supply chain resilience are now central to board-level discussions and why timely decisions on architectures and partnerships are critical to maintaining operational continuity under pressure.

How cloud transformation, cyber extortion trends, automation, and regulatory constraints are reshaping recovery architectures and strategic vendor partnerships

The landscape of data disaster recovery is shifting along several transformative axes that are redefining how organizations architect resilience. First, cloud-native and containerized workloads have made recovery planning both more granular and more distributed; recovery no longer centers solely on a datacenter failover but on application-level orchestration across multiple environments. In tandem, the rise of ransomware and other targeted extortion tactics has forced teams to prioritize rapid, immutable recovery pathways alongside enhanced detection and isolation capabilities.

Second, automation and policy-driven orchestration have moved from optional efficiencies to indispensable controls. As a result, organizations are increasingly adopting recovery playbooks that can be executed automatically, reducing human error and accelerating mean-time-to-recover. Third, regulatory expectations and cross-border data governance have introduced new constraints on where and how recovery copies may be stored and restored, prompting more nuanced decisions around data residency and encryption-in-transit and at-rest.

Finally, evolving enterprise buying behaviors and consumption models are shifting responsibility into managed services and recovery-as-a-service offerings, where contractual service level commitments and supplier transparency become decisive. Together, these shifts demand that technology leaders evaluate resilience not as a single project but as a continuous capability that requires ongoing validation, testing, and alignment with enterprise risk appetite.

Practical implications of recent tariff changes on procurement, supply resilience, and strategic choices between on-premises and cloud recovery options

Tariff adjustments and trade policy updates in 2025 have introduced new operational considerations for organizations that rely on cross-border supply chains and multinational vendor relationships for their data protection ecosystems. Changes to duties on hardware components and storage appliances influence procurement timelines and total cost of ownership for on-premises recovery infrastructures, while shifts in import regulation can ripple into vendor delivery schedules for critical replacement parts.

Beyond hardware, tariff-driven price impacts can alter the economics of hybrid deployments versus cloud-first strategies. As a consequence, procurement teams and technology leaders are revisiting their sourcing strategies to mitigate exposure to supply-side shocks and to reduce the likelihood of single-supplier dependencies. Moreover, heightened scrutiny of inbound technology flows in certain jurisdictions has prompted renewed attention to supplier audits, contractual clauses that cover compliance with trade regulations, and redundancy planning across geographic lines.

In response, recovery planners are increasingly integrating procurement intelligence into continuity plans, explicitly accounting for lead times and alternative sourcing pathways. This realignment strengthens operational resilience by ensuring that recovery appliances, licensed software, and managed-service relationships remain dependable even as tariff landscapes or trade controls fluctuate.

Targeted segmentation insights that explain how component choices, deployment models, organization size, and industry verticals reshape recovery priorities and investments

An effective segmentation lens clarifies where resilience investments deliver the greatest business value and helps leaders prioritize architecture and service choices. Based on component, market study separates Services and Solutions. The Services dimension distinguishes offerings such as Consulting And Support and Managed Services, which address governance, testing, and outsourced orchestration needs. The Solutions dimension further divides into Cloud Based, Hybrid, and On Premises approaches, reflecting differing operational trade-offs between agility, control, and data locality.

Complementing that, based on deployment model, the analysis differentiates Cloud, Hybrid, and On Premises options, each carrying distinct implications for recovery time objectives, contractual responsibility, and technical complexity. In addition, based on organization size, outcomes diverge between Large Enterprises and Small And Medium Enterprises, with larger organizations typically maintaining more complex multi-site recovery estates and smaller organizations often favoring managed services and simplified orchestration to reduce internal operational burden.

Finally, based on end user industry, distinctions emerge across verticals such as BFSI, Government, Healthcare, IT And Telecom, and Retail, where regulatory regimes, data criticality, and transaction volumes shape recovery priorities. Integrating these segmentation dimensions enables practitioners to tailor resilience programs to the combination of component choices, deployment models, organizational scale, and industry-specific constraints, thereby increasing the effectiveness and efficiency of recovery investments.

How regional regulatory regimes, infrastructure availability, and supplier ecosystems create differentiated recovery imperatives across global markets

Regional dynamics materially influence how organizations plan and operationalize data disaster recovery, and an awareness of geographic risk vectors informs both architectural decisions and vendor selection. In the Americas, regulatory maturity and the scale of enterprise IT footprints often encourage early adoption of advanced orchestration tools and multi-cloud failover arrangements, while procurement sensitivity to supply chain constraints remains a material consideration for on-premises deployments.

In Europe, Middle East & Africa, data protection and cross-border data transfer rules introduce nuanced residency and compliance demands that affect where recovery copies can be retained and how service providers must demonstrate controls. Additionally, varying levels of market maturity across the region drive a mixed adoption pattern where cloud and hybrid models coexist with localized on-premises requirements. Across Asia-Pacific, rapid digital adoption, diverse regulatory regimes, and concentrated manufacturing hubs underscore the importance of contingency planning for both cloud service continuity and hardware availability, with many organizations balancing agility with strong local redundancy strategies.

Taken together, these regional variations make it essential for resilience programs to incorporate geography-specific compliance, infrastructure availability, and supplier diversity measures. Consequently, global portfolios benefit from harmonized policies that nonetheless allow localized adaptations to address regional legal and operational realities.

Vendor and partnership dynamics that prioritize orchestration, cloud-native integration, and outcome-based managed services in modern recovery portfolios

Vendor dynamics in the data disaster recovery space increasingly center on orchestration capabilities, cloud-native integration, and transparent service commitments. Leading solution providers are investing in automation layers that abstract complex recovery workflows and link detection, isolation, and restore processes into cohesive playbooks. Meanwhile, service providers are differentiating through outcome-oriented agreements and expanded managed offerings that combine advisory, testing, and hands-on execution.

Partnerships across cloud platform vendors, software suppliers, and systems integrators play a growing role in shaping end-to-end resilience propositions. These alliances facilitate deeper native integration with public cloud primitives, enable more efficient data movement across fabrics, and support hybrid recovery patterns that span on-premises and cloud resources. Additionally, acquisition activity and strategic investments are consolidating complementary capabilities such as immutable backup storage, rapid snapshot orchestration, and forensic-ready retention features.

For enterprise buyers, the critical considerations are interoperability, open recovery APIs, and clearly defined shared responsibility boundaries. As a result, procurement and architecture teams should prioritize vendors that demonstrate strong compliance controls, verifiable recovery performance through frequent testing, and a transparent roadmap for integrating emerging technologies like infrastructure-as-code and policy-driven recovery orchestration.

Concrete governance, automation, supplier diversification, and validation steps that leaders should implement now to materially improve recovery readiness

Leaders can take several actionable steps to strengthen resilience and ensure recovery plans remain effective under evolving threats and regulatory demands. First, embed recovery objectives and testing cadence into enterprise risk governance, ensuring that business owners own the priorities for recovery time and data criticality, and that tabletop and live recovery exercises are scheduled and documented. This governance step promotes accountability and surfaces hidden dependencies across application and infrastructure teams.

Second, favor recovery architectures that include policy-driven automation and immutable recovery copies to reduce reliance on manual intervention during incidents. Transitioning to automation does not eliminate the need for human oversight, but it substantially reduces error-prone steps and shortens time to restoration. Third, diversify supplier strategies by combining native cloud resilience features with third-party orchestration and by maintaining cross-regional redundancy to mitigate supply chain or tariff-induced disruptions.

Fourth, invest in continuous validation and telemetry so that recovery readiness is measured by successful tests rather than by plan existence alone. Finally, align contractual SLAs with operational testing results and require vendors to provide demonstrable recovery workflows and transparent audit trails. Implementing these recommendations will strengthen operational readiness and allow organizations to respond more predictably when disruptions occur.

A mixed-methods research approach combining practitioner interviews, secondary documentation analysis, and scenario validation to ensure practical and evidence-based insights

A rigorous research methodology underpins the insights presented, combining structured primary engagements with secondary source synthesis and validation exercises. Primary inputs include interviews with senior IT, security, and continuity practitioners, direct discussions with infrastructure and service providers, and scenario-based tabletop reviews that illuminate decision trade-offs during real-world incident simulations. These engagements surface operational practices, procurement sensitivities, and vendor performance considerations that inform practical recommendations.

Secondary research draws on publicly available regulatory guidance, vendor technical documentation, and industry technical standards to corroborate observed patterns and to clarify compliance implications. In addition, comparative analysis across deployment models and industry verticals identifies recurring control mechanisms and failure modes. Finally, findings undergo internal validation through cross-functional expert review and scenario testing to ensure that conclusions reflect both technical feasibility and organizational realities.

This mixed-methods approach ensures that the analysis captures emerging trends, operational constraints, and pragmatic mitigation strategies while maintaining transparency about assumptions and evidence sources.

A concluding synthesis that frames modern recovery as a strategic, measurable discipline linking automation, governance, and supplier resilience to business continuity outcomes

The confluence of cloud adoption, cyber extortion threats, tariff shifts, and increasingly prescriptive regulatory frameworks has moved data disaster recovery from an operational backstop into a strategic capability. Organizations that treat recovery as an ongoing, measurable discipline-integrating automation, continuous validation, and cross-functional governance-create a durable advantage by reducing downtime, preserving customer confidence, and simplifying regulatory compliance.

Moving forward, resilience programs must balance the trade-offs between control and agility, combining cloud-native features with on-premises safeguards where necessary and employing managed services to fill capability gaps. Procurement and architecture teams should incorporate supply chain visibility and tariff-aware sourcing into continuity planning, thereby reducing vulnerability to external shocks. Ultimately, the most resilient organizations will be those that align recovery priorities with business outcomes, test assumptions frequently, and maintain diversified supplier relationships to sustain continuity under diverse stressors.

Table of Contents

1. Preface

  • 1.1. Objectives of the Study
  • 1.2. Market Definition
  • 1.3. Market Segmentation & Coverage
  • 1.4. Years Considered for the Study
  • 1.5. Currency Considered for the Study
  • 1.6. Language Considered for the Study
  • 1.7. Key Stakeholders

2. Research Methodology

  • 2.1. Introduction
  • 2.2. Research Design
    • 2.2.1. Primary Research
    • 2.2.2. Secondary Research
  • 2.3. Research Framework
    • 2.3.1. Qualitative Analysis
    • 2.3.2. Quantitative Analysis
  • 2.4. Market Size Estimation
    • 2.4.1. Top-Down Approach
    • 2.4.2. Bottom-Up Approach
  • 2.5. Data Triangulation
  • 2.6. Research Outcomes
  • 2.7. Research Assumptions
  • 2.8. Research Limitations

3. Executive Summary

  • 3.1. Introduction
  • 3.2. CXO Perspective
  • 3.3. Market Size & Growth Trends
  • 3.4. Market Share Analysis, 2025
  • 3.5. FPNV Positioning Matrix, 2025
  • 3.6. New Revenue Opportunities
  • 3.7. Next-Generation Business Models
  • 3.8. Industry Roadmap

4. Market Overview

  • 4.1. Introduction
  • 4.2. Industry Ecosystem & Value Chain Analysis
    • 4.2.1. Supply-Side Analysis
    • 4.2.2. Demand-Side Analysis
    • 4.2.3. Stakeholder Analysis
  • 4.3. Porter's Five Forces Analysis
  • 4.4. PESTLE Analysis
  • 4.5. Market Outlook
    • 4.5.1. Near-Term Market Outlook (0-2 Years)
    • 4.5.2. Medium-Term Market Outlook (3-5 Years)
    • 4.5.3. Long-Term Market Outlook (5-10 Years)
  • 4.6. Go-to-Market Strategy

5. Market Insights

  • 5.1. Consumer Insights & End-User Perspective
  • 5.2. Consumer Experience Benchmarking
  • 5.3. Opportunity Mapping
  • 5.4. Distribution Channel Analysis
  • 5.5. Pricing Trend Analysis
  • 5.6. Regulatory Compliance & Standards Framework
  • 5.7. ESG & Sustainability Analysis
  • 5.8. Disruption & Risk Scenarios
  • 5.9. Return on Investment & Cost-Benefit Analysis

6. Cumulative Impact of United States Tariffs 2025

7. Cumulative Impact of Artificial Intelligence 2025

8. Data Disaster Recovery Market, by Component

  • 8.1. Services
    • 8.1.1. Consulting And Support
    • 8.1.2. Managed Services
  • 8.2. Solutions
    • 8.2.1. Cloud Based
    • 8.2.2. Hybrid
    • 8.2.3. On Premises

9. Data Disaster Recovery Market, by Deployment Model

  • 9.1. Cloud
  • 9.2. Hybrid
  • 9.3. On Premises

10. Data Disaster Recovery Market, by Organization Size

  • 10.1. Large Enterprises
  • 10.2. Small And Medium Enterprises

11. Data Disaster Recovery Market, by End User Industry

  • 11.1. BFSI
  • 11.2. Government
  • 11.3. Healthcare
  • 11.4. IT And Telecom
  • 11.5. Retail

12. Data Disaster Recovery Market, by Region

  • 12.1. Americas
    • 12.1.1. North America
    • 12.1.2. Latin America
  • 12.2. Europe, Middle East & Africa
    • 12.2.1. Europe
    • 12.2.2. Middle East
    • 12.2.3. Africa
  • 12.3. Asia-Pacific

13. Data Disaster Recovery Market, by Group

  • 13.1. ASEAN
  • 13.2. GCC
  • 13.3. European Union
  • 13.4. BRICS
  • 13.5. G7
  • 13.6. NATO

14. Data Disaster Recovery Market, by Country

  • 14.1. United States
  • 14.2. Canada
  • 14.3. Mexico
  • 14.4. Brazil
  • 14.5. United Kingdom
  • 14.6. Germany
  • 14.7. France
  • 14.8. Russia
  • 14.9. Italy
  • 14.10. Spain
  • 14.11. China
  • 14.12. India
  • 14.13. Japan
  • 14.14. Australia
  • 14.15. South Korea

15. United States Data Disaster Recovery Market

16. China Data Disaster Recovery Market

17. Competitive Landscape

  • 17.1. Market Concentration Analysis, 2025
    • 17.1.1. Concentration Ratio (CR)
    • 17.1.2. Herfindahl Hirschman Index (HHI)
  • 17.2. Recent Developments & Impact Analysis, 2025
  • 17.3. Product Portfolio Analysis, 2025
  • 17.4. Benchmarking Analysis, 2025
  • 17.5. Acronis International GmbH
  • 17.6. Amazon Web Services, Inc.
  • 17.7. Broadcom Inc.
  • 17.8. Capgemini SE
  • 17.9. Cisco Systems, Inc.
  • 17.10. Cohesity, Inc.
  • 17.11. Commvault Systems, Inc.
  • 17.12. Dell Technologies Inc.
  • 17.13. Fujitsu Limited
  • 17.14. Hewlett Packard Enterprise Company
  • 17.15. Hitachi Vantara LLC
  • 17.16. Infosys Limited
  • 17.17. International Business Machines Corporation
  • 17.18. Iron Mountain Incorporated
  • 17.19. Microsoft Corporation
  • 17.20. NetApp, Inc.
  • 17.21. NTT DATA Group Corporation
  • 17.22. Oracle Corporation
  • 17.23. Rubrik, Inc.
  • 17.24. Tata Consultancy Services Limited
  • 17.25. Veeam Software AG
  • 17.26. Veritas Technologies LLC
  • 17.27. Wipro Limited
  • 17.28. Zerto Ltd.

LIST OF FIGURES

  • FIGURE 1. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, 2018-2032 (USD MILLION)
  • FIGURE 2. GLOBAL DATA DISASTER RECOVERY MARKET SHARE, BY KEY PLAYER, 2025
  • FIGURE 3. GLOBAL DATA DISASTER RECOVERY MARKET, FPNV POSITIONING MATRIX, 2025
  • FIGURE 4. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2025 VS 2026 VS 2032 (USD MILLION)
  • FIGURE 5. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2025 VS 2026 VS 2032 (USD MILLION)
  • FIGURE 6. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2025 VS 2026 VS 2032 (USD MILLION)
  • FIGURE 7. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2025 VS 2026 VS 2032 (USD MILLION)
  • FIGURE 8. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY REGION, 2025 VS 2026 VS 2032 (USD MILLION)
  • FIGURE 9. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY GROUP, 2025 VS 2026 VS 2032 (USD MILLION)
  • FIGURE 10. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2025 VS 2026 VS 2032 (USD MILLION)
  • FIGURE 11. UNITED STATES DATA DISASTER RECOVERY MARKET SIZE, 2018-2032 (USD MILLION)
  • FIGURE 12. CHINA DATA DISASTER RECOVERY MARKET SIZE, 2018-2032 (USD MILLION)

LIST OF TABLES

  • TABLE 1. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, 2018-2032 (USD MILLION)
  • TABLE 2. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 3. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 4. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 5. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 6. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 7. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY CONSULTING AND SUPPORT, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 8. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY CONSULTING AND SUPPORT, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 9. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY CONSULTING AND SUPPORT, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 10. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY MANAGED SERVICES, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 11. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY MANAGED SERVICES, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 12. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY MANAGED SERVICES, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 13. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 14. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 15. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 16. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 17. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY CLOUD BASED, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 18. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY CLOUD BASED, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 19. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY CLOUD BASED, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 20. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY HYBRID, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 21. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY HYBRID, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 22. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY HYBRID, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 23. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY ON PREMISES, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 24. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY ON PREMISES, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 25. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY ON PREMISES, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 26. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 27. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY CLOUD, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 28. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY CLOUD, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 29. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY CLOUD, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 30. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY HYBRID, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 31. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY HYBRID, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 32. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY HYBRID, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 33. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY ON PREMISES, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 34. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY ON PREMISES, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 35. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY ON PREMISES, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 36. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 37. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY LARGE ENTERPRISES, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 38. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY LARGE ENTERPRISES, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 39. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY LARGE ENTERPRISES, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 40. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY SMALL AND MEDIUM ENTERPRISES, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 41. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY SMALL AND MEDIUM ENTERPRISES, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 42. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY SMALL AND MEDIUM ENTERPRISES, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 43. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 44. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY BFSI, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 45. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY BFSI, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 46. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY BFSI, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 47. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY GOVERNMENT, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 48. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY GOVERNMENT, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 49. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY GOVERNMENT, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 50. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY HEALTHCARE, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 51. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY HEALTHCARE, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 52. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY HEALTHCARE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 53. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY IT AND TELECOM, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 54. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY IT AND TELECOM, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 55. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY IT AND TELECOM, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 56. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY RETAIL, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 57. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY RETAIL, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 58. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY RETAIL, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 59. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY REGION, 2018-2032 (USD MILLION)
  • TABLE 60. AMERICAS DATA DISASTER RECOVERY MARKET SIZE, BY SUBREGION, 2018-2032 (USD MILLION)
  • TABLE 61. AMERICAS DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 62. AMERICAS DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 63. AMERICAS DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 64. AMERICAS DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 65. AMERICAS DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 66. AMERICAS DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 67. NORTH AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 68. NORTH AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 69. NORTH AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 70. NORTH AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 71. NORTH AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 72. NORTH AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 73. NORTH AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 74. LATIN AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 75. LATIN AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 76. LATIN AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 77. LATIN AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 78. LATIN AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 79. LATIN AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 80. LATIN AMERICA DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 81. EUROPE, MIDDLE EAST & AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY SUBREGION, 2018-2032 (USD MILLION)
  • TABLE 82. EUROPE, MIDDLE EAST & AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 83. EUROPE, MIDDLE EAST & AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 84. EUROPE, MIDDLE EAST & AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 85. EUROPE, MIDDLE EAST & AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 86. EUROPE, MIDDLE EAST & AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 87. EUROPE, MIDDLE EAST & AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 88. EUROPE DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 89. EUROPE DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 90. EUROPE DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 91. EUROPE DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 92. EUROPE DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 93. EUROPE DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 94. EUROPE DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 95. MIDDLE EAST DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 96. MIDDLE EAST DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 97. MIDDLE EAST DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 98. MIDDLE EAST DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 99. MIDDLE EAST DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 100. MIDDLE EAST DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 101. MIDDLE EAST DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 102. AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 103. AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 104. AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 105. AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 106. AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 107. AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 108. AFRICA DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 109. ASIA-PACIFIC DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 110. ASIA-PACIFIC DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 111. ASIA-PACIFIC DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 112. ASIA-PACIFIC DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 113. ASIA-PACIFIC DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 114. ASIA-PACIFIC DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 115. ASIA-PACIFIC DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 116. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY GROUP, 2018-2032 (USD MILLION)
  • TABLE 117. ASEAN DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 118. ASEAN DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 119. ASEAN DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 120. ASEAN DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 121. ASEAN DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 122. ASEAN DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 123. ASEAN DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 124. GCC DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 125. GCC DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 126. GCC DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 127. GCC DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 128. GCC DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 129. GCC DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 130. GCC DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 131. EUROPEAN UNION DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 132. EUROPEAN UNION DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 133. EUROPEAN UNION DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 134. EUROPEAN UNION DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 135. EUROPEAN UNION DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 136. EUROPEAN UNION DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 137. EUROPEAN UNION DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 138. BRICS DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 139. BRICS DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 140. BRICS DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 141. BRICS DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 142. BRICS DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 143. BRICS DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 144. BRICS DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 145. G7 DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 146. G7 DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 147. G7 DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 148. G7 DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 149. G7 DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 150. G7 DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 151. G7 DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 152. NATO DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 153. NATO DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 154. NATO DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 155. NATO DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 156. NATO DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 157. NATO DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 158. NATO DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 159. GLOBAL DATA DISASTER RECOVERY MARKET SIZE, BY COUNTRY, 2018-2032 (USD MILLION)
  • TABLE 160. UNITED STATES DATA DISASTER RECOVERY MARKET SIZE, 2018-2032 (USD MILLION)
  • TABLE 161. UNITED STATES DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 162. UNITED STATES DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 163. UNITED STATES DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 164. UNITED STATES DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 165. UNITED STATES DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 166. UNITED STATES DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)
  • TABLE 167. CHINA DATA DISASTER RECOVERY MARKET SIZE, 2018-2032 (USD MILLION)
  • TABLE 168. CHINA DATA DISASTER RECOVERY MARKET SIZE, BY COMPONENT, 2018-2032 (USD MILLION)
  • TABLE 169. CHINA DATA DISASTER RECOVERY MARKET SIZE, BY SERVICES, 2018-2032 (USD MILLION)
  • TABLE 170. CHINA DATA DISASTER RECOVERY MARKET SIZE, BY SOLUTIONS, 2018-2032 (USD MILLION)
  • TABLE 171. CHINA DATA DISASTER RECOVERY MARKET SIZE, BY DEPLOYMENT MODEL, 2018-2032 (USD MILLION)
  • TABLE 172. CHINA DATA DISASTER RECOVERY MARKET SIZE, BY ORGANIZATION SIZE, 2018-2032 (USD MILLION)
  • TABLE 173. CHINA DATA DISASTER RECOVERY MARKET SIZE, BY END USER INDUSTRY, 2018-2032 (USD MILLION)