資料網格市場 - 全球產業規模、佔有率、趨勢、機會和預測（按組件、按部署類型、按最終用戶、按地區和競爭細分，2020-2030 年預測）

2024 年全球資料網格市場價值為 15.6 億美元，預計到 2030 年將達到 38.9 億美元，預測期內複合年成長率為 16.26%。

資料網格市場是一個由技術、平台和服務組成的生態系統，旨在幫助企業實現去中心化的資料管理和分析方法。與資料湖或資料倉儲等傳統的中心化資料架構不同，資料網格框架使各個業務領域能夠擁有、管理和提供其資料產品，同時保持整個企業的互通性和治理能力。這種模式轉變解決了大型企業在擴展分析能力方面所面臨的挑戰，因為中心化資料系統通常會造成瓶頸、延遲和治理複雜性。

資料網格市場涵蓋促進資料發現、編目和治理的軟體平台；協助實施、整合和支援的服務；以及幫助組織過渡到面向領域的資料所有權模型的培訓和諮詢解決方案。該市場的成長由多種因素驅動。首先，企業擴大處理大量結構化和非結構化資料，使得集中式系統不足以進行即時決策和特定領域的分析。其次，雲端運算、邊緣運算和微服務架構的興起使得將資料所有權和處理分佈到更靠近源頭的地方變得可行且可取。

企業正在尋求透過賦予各個團隊工具和責任來管理自己的資料管道，從而提高敏捷性、減少資料孤島並加速洞察。此外，出於法規遵循、資料安全和隱私方面的考慮，企業正在採用能夠加強治理並允許去中心化控制的框架。人工智慧驅動的資料管理、自動化元資料編目和整合平台即服務等技術創新也透過簡化複雜的資料操作，促進了市場的擴張。

銀行、金融服務、醫療保健、零售、製造和電信等關鍵垂直行業正在迅速採用資料網格原則，以提升營運效率、客戶洞察和產品創新。隨著企業持續優先考慮資料民主化、自助式分析和可擴展架構，預計資料網格市場將在未來幾年實現顯著成長，這既得益於技術進步，也得益於將資料作為關鍵企業資產的策略需求的不斷發展。

關鍵市場促進因素

對深度偽造和虛假資訊的擔憂日益加劇，推動數據網格市場發展

主要市場挑戰

實施和組織變革的複雜性

主要市場趨勢

雲端原生和混合架構的採用日益增多

目錄

第 1 章：產品概述

第2章：研究方法

第3章：執行摘要

第4章：顧客之聲

第5章：全球資料網格市場展望

• 市場規模和預測
  • 按價值
• 市場佔有率和預測
  • 按組件（平台、服務）
  • 依部署類型（本機、雲端）
  • 按最終用戶（銀行、金融服務和保險、資訊科技和電信、醫療保健和生命科學、零售和電子商務、製造業、政府和公共部門、其他）
  • 按地區（北美、歐洲、南美、中東和非洲、亞太地區）
• 按公司分類（2024 年）
• 市場地圖

第6章：北美資料網格市場展望

• 市場規模和預測
• 市場佔有率和預測
• 北美：國家分析
  • 美國
  • 加拿大
  • 墨西哥

第7章：歐洲資料網格市場展望

• 市場規模和預測
• 市場佔有率和預測
• 歐洲：國家分析
  • 德國
  • 法國
  • 英國
  • 義大利
  • 西班牙

第8章：亞太資料網格市場展望

• 市場規模和預測
• 市場佔有率和預測
• 亞太地區：國家分析
  • 中國
  • 印度
  • 日本
  • 韓國
  • 澳洲

第9章：中東和非洲資料網格市場展望

• 市場規模和預測
• 市場佔有率和預測
• 中東和非洲：國家分析
  • 沙烏地阿拉伯
  • 阿拉伯聯合大公國
  • 南非

第10章：南美洲資料網格市場展望

• 市場規模和預測
• 市場佔有率和預測
• 南美洲：國家分析
  • 巴西
  • 哥倫比亞
  • 阿根廷

第 11 章：市場動態

• 驅動程式
• 挑戰

第 12 章：市場趨勢與發展

• 合併與收購（如有）
• 產品發布（如有）
• 最新動態

第13章：公司簡介

• Snowflake Inc.
• Databricks, Inc.
• IBM Corporation
• Microsoft Corporation
• Oracle Corporation
• Google LLC
• Amazon Web Services, Inc.
• Cloudera, Inc.
• QlikTech International AB
• Talend SA

第 14 章：策略建議

第15章調查會社について,免責事項

The Global Data Mesh Market was valued at USD 1.56 billion in 2024 and is expected to reach USD 3.89 billion by 2030 with a CAGR of 16.26% during the forecast period.

The Data Mesh Market refers to the ecosystem of technologies, platforms, and services that enable organizations to implement a decentralized approach to data management and analytics. Unlike traditional centralized data architectures such as data lakes or data warehouses, the data mesh framework empowers individual business domains to own, manage, and serve their data as products, while maintaining interoperability and governance across the enterprise. This paradigm shift addresses the challenges of scaling analytics in large organizations, where centralized data systems often create bottlenecks, delays, and governance complexities.

The Data Mesh Market encompasses software platforms that facilitate data discovery, cataloging, and governance; services that assist in implementation, integration, and support; and training and consultancy solutions that help organizations transition to domain-oriented data ownership models. The growth of this market is driven by several factors. Firstly, enterprises are increasingly dealing with massive volumes of structured and unstructured data, making centralized systems insufficient for real-time decision-making and domain-specific analytics. Secondly, the rise of cloud computing, edge computing, and microservices architectures has made it feasible and desirable to distribute data ownership and processing closer to the source.

Organizations are seeking to improve agility, reduce data silos, and accelerate insights by empowering individual teams with the tools and responsibility to manage their own data pipelines. Additionally, regulatory compliance, data security, and privacy considerations are prompting businesses to adopt frameworks that enforce governance while allowing decentralized control. Technological innovations such as AI-driven data management, automated metadata cataloging, and integration platforms as a service are also contributing to the market's expansion by simplifying complex data operations.

Key industry verticals including banking, financial services, healthcare, retail, manufacturing, and telecommunications are rapidly adopting data mesh principles to enhance operational efficiency, customer insights, and product innovation. As organizations continue to prioritize data democratization, self-service analytics, and scalable architectures, the Data Mesh Market is expected to witness significant growth in the coming years, driven by both technological advancements and the evolving strategic imperative to leverage data as a critical enterprise asset.

Key Market Drivers

Rising Concerns Over Deepfakes and Misinformation Driving the Data Mesh Market

In the rapidly evolving digital ecosystem, the escalating concerns surrounding deepfakes and misinformation emerge as a primary driver accelerating the Data Mesh Market, as organizations and governments alike confront the pervasive threat of manipulated media that undermines trust, sows discord, and amplifies societal divisions, necessitating advanced detection technologies to authenticate content and safeguard information integrity. This driver is underscored by the proliferation of synthetic media generated through sophisticated artificial intelligence tools, which can convincingly alter videos, audio, and images to fabricate events, impersonate individuals, or spread false narratives, thereby eroding public confidence in digital platforms and traditional media outlets.

Industries ranging from journalism to finance are particularly vulnerable, where deepfakes can manipulate stock markets through falsified executive statements or incite political unrest via doctored footage of public figures, compelling stakeholders to invest in robust Data Mesh systems that employ machine learning algorithms to analyze anomalies in pixel patterns, audio waveforms, and metadata inconsistencies. The market's growth is further propelled by the exponential increase in user-generated content on social media, where misinformation campaigns can virally disseminate unchecked, leading to real-world consequences such as election interference or public health crises, as evidenced by fabricated health advisories during global events.

Enterprises are responding by integrating Data Mesh into their moderation workflows, utilizing real-time scanning tools that flag suspicious uploads before they gain traction, thus mitigating reputational risks and legal liabilities associated with hosting harmful material. Regulatory bodies are also intensifying scrutiny, mandating platforms to deploy proactive detection measures to combat disinformation, which in turn stimulates demand for scalable solutions that balance efficacy with ethical considerations like privacy preservation. Small and medium-sized businesses, often lacking in-house expertise, are turning to cloud-based Data Mesh services that offer pay-per-use models, democratizing access to enterprise-level defenses against deepfake incursions.

The convergence of this technology with blockchain for immutable content verification adds another layer of assurance, enabling traceable provenance that counters alteration attempts. Cultural shifts toward media literacy amplify this driver, as educated consumers demand verifiable sources, pressuring content providers to adopt detection protocols that enhance transparency and foster user loyalty. Economic incentives align as well, with insurers offering reduced premiums for platforms demonstrating robust anti-deepfake measures, incentivizing widespread adoption.

In volatile geopolitical landscapes, nation-state actors exploit misinformation for hybrid warfare, heightening the imperative for detection tools that incorporate geopolitical context in threat modeling. Collaborative ecosystems between tech vendors and academic institutions accelerate innovation, yielding hybrid models that combine neural networks with human oversight for superior accuracy in nuanced scenarios. Sustainability in detection practices emerges as a consideration, with energy-efficient algorithms addressing the computational demands of large-scale scanning.

Workforce development through specialized training programs equips analysts to interpret detection outputs, bridging the skills gap in this nascent field. Ultimately, this driver encapsulates the Data Mesh Market's pivotal role in restoring faith in the digital realm, where proactive identification of deepfakes and misinformation not only protects assets but also upholds democratic values, drives technological advancement, and unlocks new avenues for secure content monetization in an era dominated by information warfare.

Deepfake fraud incidents increased tenfold between 2022 and 2023, with 500,000 video and voice deepfakes shared on social media in 2023 alone. Additionally, 80% of Telegram channels contain deepfake content, while 26% of people encountered a deepfake scam online in 2024, and 77% of victims lost money, with one-third losing over USD 1,000. These figures underscore the urgent need for advanced detection technologies amid rising synthetic media threats.

Key Market Challenges

Complexity of Implementation and Organizational Change

One of the primary challenges facing the Data Mesh Market is the inherent complexity of implementing a decentralized data architecture within large enterprises. Transitioning from traditional centralized data warehouses or data lakes to a domain-oriented data mesh model requires significant structural, technological, and cultural changes. Organizations must reorganize teams to adopt domain ownership of data, which often involves redefining roles, responsibilities, and reporting structures. Moreover, existing legacy systems may not seamlessly integrate with new data mesh platforms, requiring costly and time-consuming modernization efforts.

The technological integration itself is complicated, as data pipelines, APIs, metadata catalogs, and governance tools must all be aligned across distributed domains. Enterprises also face the challenge of training personnel to adopt new skill sets, including data product ownership, domain-oriented analytics, and cross-domain collaboration. Resistance to change among employees and stakeholders can slow adoption, while misalignment between business units may undermine the intended benefits of decentralization. Consequently, the complexity of both organizational and technical implementation remains a significant barrier that may limit the rate at which the Data Mesh Market expands.

Key Market Trends

Growing Adoption of Cloud-Native and Hybrid Architectures

One of the most significant trends in the Data Mesh Market is the accelerating adoption of cloud-native and hybrid data architectures. Organizations are increasingly moving away from monolithic, centralized data warehouses and embracing distributed cloud infrastructures that support scalable, domain-oriented data operations. Cloud platforms offer the flexibility to deploy data mesh frameworks across multiple regions, integrate with various services, and scale resources on demand, allowing enterprises to manage and process large volumes of structured and unstructured data efficiently.

Hybrid architectures, combining on-premises systems with cloud deployments, are also gaining traction as businesses seek to balance control, security, and cost-effectiveness. By leveraging cloud-native tools such as containerization, microservices, and orchestration platforms, organizations can enable real-time data access, seamless integration of multiple domains, and faster delivery of analytics insights. This trend is further reinforced by the increasing adoption of artificial intelligence and machine learning technologies within cloud ecosystems, which enhance the automation, quality, and usability of decentralized data products.

Additionally, cloud-native and hybrid approaches facilitate collaboration between business and technology teams, as data can be shared, governed, and monitored efficiently across domains. As enterprises continue to prioritize agility, resilience, and scalability, the integration of cloud-native and hybrid architectures is expected to drive the expansion and modernization of the Data Mesh Market in the coming years.

Key Market Players

• Snowflake Inc.
• Databricks, Inc.
• IBM Corporation
• Microsoft Corporation
• Oracle Corporation
• Google LLC
• Amazon Web Services, Inc.
• Cloudera, Inc.
• QlikTech International AB
• Talend S.A.

Report Scope:

In this report, the Global Data Mesh Market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Data Mesh Market, By Component:

• Platforms
• Services

Data Mesh Market, By Deployment Type:

• On-Premises
• Cloud

Data Mesh Market, By End-User:

• Banking, Financial Services, and Insurance
• Information Technology and Telecommunications
• Healthcare and Life Sciences
• Retail and E-Commerce
• Manufacturing
• Government and Public Sector
• Others

Data Mesh Market, By Region:

• North America
  • United States
  • Canada
  • Mexico
• Europe
  • Germany
  • France
  • United Kingdom
  • Italy
  • Spain
• South America
  • Brazil
  • Argentina
  • Colombia
• Asia-Pacific
  • China
  • India
  • Japan
  • South Korea
  • Australia
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • South Africa

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Data Mesh Market.

Available Customizations:

Global Data Mesh Market report with the given market data, TechSci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

• Detailed analysis and profiling of additional market players (up to five).

Table of Contents

1. Product Overview

• 1.1. Market Definition
• 1.2. Scope of the Market
  • 1.2.1. Markets Covered
  • 1.2.2. Years Considered for Study
  • 1.2.3. Key Market Segmentations

2. Research Methodology

• 2.1. Objective of the Study
• 2.2. Baseline Methodology
• 2.3. Key Industry Partners
• 2.4. Major Association and Secondary Sources
• 2.5. Forecasting Methodology
• 2.6. Data Triangulation & Validation
• 2.7. Assumptions and Limitations

3. Executive Summary

• 3.1. Overview of the Market
• 3.2. Overview of Key Market Segmentations
• 3.3. Overview of Key Market Players
• 3.4. Overview of Key Regions/Countries
• 3.5. Overview of Market Drivers, Challenges, and Trends

4. Voice of Customer

5. Global Data Mesh Market Outlook

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. Market Share & Forecast
  • 5.2.1. By Component (Platforms, Services)
  • 5.2.2. By Deployment Type (On-Premises, Cloud)
  • 5.2.3. By End-User (Banking, Financial Services, and Insurance, Information Technology and Telecommunications, Healthcare and Life Sciences, Retail and E-Commerce, Manufacturing, Government and Public Sector, Others)
  • 5.2.4. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)
• 5.3. By Company (2024)
• 5.4. Market Map

6. North America Data Mesh Market Outlook

• 6.1. Market Size & Forecast
  • 6.1.1. By Value
• 6.2. Market Share & Forecast
  • 6.2.1. By Component
  • 6.2.2. By Deployment Type
  • 6.2.3. By End-User
  • 6.2.4. By Country
• 6.3. North America: Country Analysis
  • 6.3.1. United States Data Mesh Market Outlook
    • 6.3.1.1. Market Size & Forecast
      • 6.3.1.1.1. By Value
    • 6.3.1.2. Market Share & Forecast
      • 6.3.1.2.1. By Component
      • 6.3.1.2.2. By Deployment Type
      • 6.3.1.2.3. By End-User
  • 6.3.2. Canada Data Mesh Market Outlook
    • 6.3.2.1. Market Size & Forecast
      • 6.3.2.1.1. By Value
    • 6.3.2.2. Market Share & Forecast
      • 6.3.2.2.1. By Component
      • 6.3.2.2.2. By Deployment Type
      • 6.3.2.2.3. By End-User
  • 6.3.3. Mexico Data Mesh Market Outlook
    • 6.3.3.1. Market Size & Forecast
      • 6.3.3.1.1. By Value
    • 6.3.3.2. Market Share & Forecast
      • 6.3.3.2.1. By Component
      • 6.3.3.2.2. By Deployment Type
      • 6.3.3.2.3. By End-User

7. Europe Data Mesh Market Outlook

• 7.1. Market Size & Forecast
  • 7.1.1. By Value
• 7.2. Market Share & Forecast
  • 7.2.1. By Component
  • 7.2.2. By Deployment Type
  • 7.2.3. By End-User
  • 7.2.4. By Country
• 7.3. Europe: Country Analysis
  • 7.3.1. Germany Data Mesh Market Outlook
    • 7.3.1.1. Market Size & Forecast
      • 7.3.1.1.1. By Value
    • 7.3.1.2. Market Share & Forecast
      • 7.3.1.2.1. By Component
      • 7.3.1.2.2. By Deployment Type
      • 7.3.1.2.3. By End-User
  • 7.3.2. France Data Mesh Market Outlook
    • 7.3.2.1. Market Size & Forecast
      • 7.3.2.1.1. By Value
    • 7.3.2.2. Market Share & Forecast
      • 7.3.2.2.1. By Component
      • 7.3.2.2.2. By Deployment Type
      • 7.3.2.2.3. By End-User
  • 7.3.3. United Kingdom Data Mesh Market Outlook
    • 7.3.3.1. Market Size & Forecast
      • 7.3.3.1.1. By Value
    • 7.3.3.2. Market Share & Forecast
      • 7.3.3.2.1. By Component
      • 7.3.3.2.2. By Deployment Type
      • 7.3.3.2.3. By End-User
  • 7.3.4. Italy Data Mesh Market Outlook
    • 7.3.4.1. Market Size & Forecast
      • 7.3.4.1.1. By Value
    • 7.3.4.2. Market Share & Forecast
      • 7.3.4.2.1. By Component
      • 7.3.4.2.2. By Deployment Type
      • 7.3.4.2.3. By End-User
  • 7.3.5. Spain Data Mesh Market Outlook
    • 7.3.5.1. Market Size & Forecast
      • 7.3.5.1.1. By Value
    • 7.3.5.2. Market Share & Forecast
      • 7.3.5.2.1. By Component
      • 7.3.5.2.2. By Deployment Type
      • 7.3.5.2.3. By End-User

8. Asia Pacific Data Mesh Market Outlook

• 8.1. Market Size & Forecast
  • 8.1.1. By Value
• 8.2. Market Share & Forecast
  • 8.2.1. By Component
  • 8.2.2. By Deployment Type
  • 8.2.3. By End-User
  • 8.2.4. By Country
• 8.3. Asia Pacific: Country Analysis
  • 8.3.1. China Data Mesh Market Outlook
    • 8.3.1.1. Market Size & Forecast
      • 8.3.1.1.1. By Value
    • 8.3.1.2. Market Share & Forecast
      • 8.3.1.2.1. By Component
      • 8.3.1.2.2. By Deployment Type
      • 8.3.1.2.3. By End-User
  • 8.3.2. India Data Mesh Market Outlook
    • 8.3.2.1. Market Size & Forecast
      • 8.3.2.1.1. By Value
    • 8.3.2.2. Market Share & Forecast
      • 8.3.2.2.1. By Component
      • 8.3.2.2.2. By Deployment Type
      • 8.3.2.2.3. By End-User
  • 8.3.3. Japan Data Mesh Market Outlook
    • 8.3.3.1. Market Size & Forecast
      • 8.3.3.1.1. By Value
    • 8.3.3.2. Market Share & Forecast
      • 8.3.3.2.1. By Component
      • 8.3.3.2.2. By Deployment Type
      • 8.3.3.2.3. By End-User
  • 8.3.4. South Korea Data Mesh Market Outlook
    • 8.3.4.1. Market Size & Forecast
      • 8.3.4.1.1. By Value
    • 8.3.4.2. Market Share & Forecast
      • 8.3.4.2.1. By Component
      • 8.3.4.2.2. By Deployment Type
      • 8.3.4.2.3. By End-User
  • 8.3.5. Australia Data Mesh Market Outlook
    • 8.3.5.1. Market Size & Forecast
      • 8.3.5.1.1. By Value
    • 8.3.5.2. Market Share & Forecast
      • 8.3.5.2.1. By Component
      • 8.3.5.2.2. By Deployment Type
      • 8.3.5.2.3. By End-User

9. Middle East & Africa Data Mesh Market Outlook

• 9.1. Market Size & Forecast
  • 9.1.1. By Value
• 9.2. Market Share & Forecast
  • 9.2.1. By Component
  • 9.2.2. By Deployment Type
  • 9.2.3. By End-User
  • 9.2.4. By Country
• 9.3. Middle East & Africa: Country Analysis
  • 9.3.1. Saudi Arabia Data Mesh Market Outlook
    • 9.3.1.1. Market Size & Forecast
      • 9.3.1.1.1. By Value
    • 9.3.1.2. Market Share & Forecast
      • 9.3.1.2.1. By Component
      • 9.3.1.2.2. By Deployment Type
      • 9.3.1.2.3. By End-User
  • 9.3.2. UAE Data Mesh Market Outlook
    • 9.3.2.1. Market Size & Forecast
      • 9.3.2.1.1. By Value
    • 9.3.2.2. Market Share & Forecast
      • 9.3.2.2.1. By Component
      • 9.3.2.2.2. By Deployment Type
      • 9.3.2.2.3. By End-User
  • 9.3.3. South Africa Data Mesh Market Outlook
    • 9.3.3.1. Market Size & Forecast
      • 9.3.3.1.1. By Value
    • 9.3.3.2. Market Share & Forecast
      • 9.3.3.2.1. By Component
      • 9.3.3.2.2. By Deployment Type
      • 9.3.3.2.3. By End-User

10. South America Data Mesh Market Outlook

• 10.1. Market Size & Forecast
  • 10.1.1. By Value
• 10.2. Market Share & Forecast
  • 10.2.1. By Component
  • 10.2.2. By Deployment Type
  • 10.2.3. By End-User
  • 10.2.4. By Country
• 10.3. South America: Country Analysis
  • 10.3.1. Brazil Data Mesh Market Outlook
    • 10.3.1.1. Market Size & Forecast
      • 10.3.1.1.1. By Value
    • 10.3.1.2. Market Share & Forecast
      • 10.3.1.2.1. By Component
      • 10.3.1.2.2. By Deployment Type
      • 10.3.1.2.3. By End-User
  • 10.3.2. Colombia Data Mesh Market Outlook
    • 10.3.2.1. Market Size & Forecast
      • 10.3.2.1.1. By Value
    • 10.3.2.2. Market Share & Forecast
      • 10.3.2.2.1. By Component
      • 10.3.2.2.2. By Deployment Type
      • 10.3.2.2.3. By End-User
  • 10.3.3. Argentina Data Mesh Market Outlook
    • 10.3.3.1. Market Size & Forecast
      • 10.3.3.1.1. By Value
    • 10.3.3.2. Market Share & Forecast
      • 10.3.3.2.1. By Component
      • 10.3.3.2.2. By Deployment Type
      • 10.3.3.2.3. By End-User

11. Market Dynamics

• 11.1. Drivers
• 11.2. Challenges

12. Market Trends and Developments

• 12.1. Merger & Acquisition (If Any)
• 12.2. Product Launches (If Any)
• 12.3. Recent Developments

13. Company Profiles

• 13.1. Snowflake Inc.
  • 13.1.1. Business Overview
  • 13.1.2. Key Revenue and Financials
  • 13.1.3. Recent Developments
  • 13.1.4. Key Personnel
  • 13.1.5. Key Product/Services Offered
• 13.2. Databricks, Inc.
• 13.3. IBM Corporation
• 13.4. Microsoft Corporation
• 13.5. Oracle Corporation
• 13.6. Google LLC
• 13.7. Amazon Web Services, Inc.
• 13.8. Cloudera, Inc.
• 13.9. QlikTech International AB
• 13.10. Talend S.A.

14. Strategic Recommendations

15. About Us & Disclaimer