查看購物車
  • English
  • Japanese
封面
市場調查報告書
商品編碼
1918496

資料災害復原市場按組件、部署模式、組織規模和最終用戶產業分類 - 全球預測 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個工作天內

價格

※ 本網頁內容可能與最新版本有所差異。詳細情況請與我們聯繫。

預計到 2025 年，資料災害復原市場規模將達到 1.9,247 億美元，到 2026 年將成長至 2.1117 億美元，到 2032 年將達到 3.4863 億美元，複合年成長率為 8.85%。

關鍵市場統計數據
基準年 2025 1.9247億美元
預計年份：2026年 2.1117億美元
預測年份 2032 3.4863億美元
複合年成長率 (%) 8.85%

本文簡要概述了現代資料連續性面臨的挑戰、管治的改變，以及為何復原策略現在需要跨職能的業務協作。

現代企業面臨的資料連續性環境比過去幾十年複雜得多。分散式雲端原生應用、廣泛的遠端辦公以及關鍵任務資料在混合基礎設施上的日益增多，都擴大了攻擊面，也增加了發生事件時必須維護的業務依賴性。因此，資料災害復原已從單一的技術學科發展成為一項跨職能的業務能力，與收入連續性、合規性和客戶信任息息相關。

雲端轉型、網路威脅趨勢、自動化和監管限制正在重塑恢復架構和策略供應商夥伴關係。

資料災害復原格局正沿著多個變革軸發生轉變，重新定義企業建構韌性的方式。首先，雲端原生和容器化工作負載使得復原計畫更加分散和去中心化。復原不再僅依賴資料中心容錯移轉，而是圍繞著跨多個環境的應用層級編配。同時，勒索軟體和其他定向勒索手段的興起迫使團隊在增強檢測和遏制能力的同時，優先考慮快速及時的恢復路徑。

近期關稅調整對採購、供應鏈韌性以及本地部署和雲端恢復方案之間的策略選擇所產生的實際影響

2025 年的關稅調整和貿易政策更新為那些資料保護生態系統依賴跨境供應鏈和跨國供應商關係的組織帶來了新的營運考量。硬體組件和儲存設備關稅的變化將影響本地恢復基礎設施的採購計劃和整體擁有成本，而進口法規的波動則可能對關鍵替換零件的供應商交貨時間產生影響。

有針對性的細分洞察，解釋了組件選擇、部署模式、組織規模和行業細分將如何重塑復甦優先事項和投資。

有效的細分觀點能夠明確彈性投資在哪些方面能夠帶來最大的業務價值，並幫助領導者確定架構和服務選擇的優先順序。市場調查根據組件將“服務”和“解決方案”區分開來。 「服務」維度區分了不同的交付類型，例如諮詢/支援和託管服務，這些服務滿足管治、測試和外包編配需求。 「解決方案」維度進一步細分為雲端、混合和本地部署三種方式，反映了敏捷性、控制和資料本地性之間不同的營運權衡。

區域管理體制、基礎設施可用性和供應商生態系統如何導致全球市場差異化的復甦需求

區域趨勢對組織如何規劃和實施資料災害復原有顯著影響。地理風險因素的認知體現在架構決策和供應商選擇兩個面向。在美洲，監管成熟度和企業IT基礎設施規模往往促使企業儘早採用進階編配工具和多重雲端容錯移轉配置。同時，由於供應鏈限制，採購的考量仍然是本地部署的關鍵因素。

在現代恢復方案中，供應商和夥伴關係的趨勢是優先考慮編配、雲端原生整合和基於結果的託管服務。

資料災害復原領域的供應商發展趨勢日益側重於編配能力、雲端原生整合和透明的服務承諾。領先的解決方案供應商正在投資自動化層，以抽象化複雜的復原工作流程，並將檢測、遏制和復原流程整合到統一的劇本中。同時，服務供應商正透過以結果為導向的合約和擴展的託管服務產品來實現差異化，這些產品融合了諮詢、測試和實際操作。

領導企業現在應該採取哪些具體的管治、自動化、供應商多元化和檢驗措施，以大幅提高災後復原準備能力？

領導者可以採取多項切實可行的措施來增強韌性，確保復原計畫在不斷變化的威脅和監管要求下保持有效。首先，將復原目標和測試節奏納入企業風險管治，確保業務負責人明確恢復時間和資料關鍵性的優先級，並確保桌面演練和即時復原演練都得到規劃和記錄。這個管治步驟有助於提升課責，並揭示應用團隊和基礎架構團隊之間隱藏的依賴關係。

結合從業者訪談、第二手資料分析和情境檢驗的混合調查方法，確保了研究結果的實用性和實證性。

研究結果以嚴謹的調查方法為支撐，該方法結合了結構化的初步研究以及對二級資訊來源的整合與檢驗。一級資訊來源包括對高級IT、安全和業務永續營運負責人的訪談；與基礎設施和服務供應商的面對面交流；以及基於情境的案頭研究，旨在揭示在真實事件模擬過程中決策的權衡取捨。這些負責人揭示了營運實務、採購考量和供應商績效考量，為提出切實可行的建議奠定了基礎。

一項綜合分析，將現代恢復定位為一項策略性和可衡量的學科，它將自動化、管治和供應商韌性與業務永續營運成果聯繫起來。

雲端運算普及率不斷提高、網路威脅日益成長、資費波動以及法規結構日益嚴格等因素的綜合影響，已使資料災害復原從單純的營運保障轉變為一項戰略能力。那些將資料復原視為一項持續、可衡量的機制，並整合自動化、持續檢驗和跨職能管治的企業，能夠透過減少停機時間、維護客戶信任和簡化合規流程，創造永續的競爭優勢。

目錄

第1章：序言

第2章調查方法

  • 研究設計
  • 研究框架
  • 市場規模預測
  • 數據三角測量
  • 調查結果
  • 調查前提
  • 調查限制

第3章執行摘要

  • 首席體驗長觀點
  • 市場規模和成長趨勢
  • 2025年市佔率分析
  • FPNV定位矩陣，2025
  • 新的商機
  • 下一代經營模式
  • 產業藍圖

第4章 市場概覽

  • 產業生態系與價值鏈分析
  • 波特五力分析
  • PESTEL 分析
  • 市場展望
  • 上市策略

第5章 市場洞察

  • 消費者洞察與終端用戶觀點
  • 消費者體驗基準
  • 機會地圖
  • 分銷通路分析
  • 價格趨勢分析
  • 監理合規和標準框架
  • ESG與永續性分析
  • 中斷和風險情景
  • 投資報酬率和成本效益分析

第6章：美國關稅的累積影響，2025年

第7章：人工智慧的累積影響，2025年

8. 資料災害復原市場（依組件分類）

  • 服務
    • 諮詢與支持
    • 託管服務
  • 解決方案
    • 基於雲端的
    • 混合
    • 本地部署

9. 依部署模式分類的資料災害復原市場

  • 雲
  • 混合
  • 本地部署

第10章：依組織規模分類的資料災害復原市場

  • 主要企業
  • 小型企業

第11章：以最終用戶產業分類的資料災害復原市場

  • BFSI
  • 政府
  • 衛生保健
  • 資訊科技/通訊
  • 零售

第12章：按地區分類的資料災害復原市場

  • 美洲
    • 北美洲
    • 拉丁美洲
  • 歐洲、中東和非洲
    • 歐洲
    • 中東
    • 非洲
  • 亞太地區

第13章：按組別分類的資料災害復原市場

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

第14章：各國資料災害復原市場

  • 美國
  • 加拿大
  • 墨西哥
  • 巴西
  • 英國
  • 德國
  • 法國
  • 俄羅斯
  • 義大利
  • 西班牙
  • 中國
  • 印度
  • 日本
  • 澳洲
  • 韓國

第15章美國資料災害復原市場

第16章：中國資料災害復原市場

第17章 競爭格局

  • 市場集中度分析，2025年
    • 濃度比（CR）
    • 赫芬達爾-赫希曼指數 (HHI)
  • 近期趨勢及影響分析，2025 年
  • 2025年產品系列分析
  • 基準分析，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)