The Worldwide Data Fabric Industry is Expected to Reach $4.2 Billion by 2026 at a CAGR of 26.3% from 2020

The “Data Fabric Market by Type (Disk-Based, In-Memory), Business Applications (Fraud Detection and Security Management, Customer Experience Management, Business Process Management, GRC Management), Service, Vertical and Region – Global Forecast to 2026” report has been added to’s offering.

The global Data fabric market size to grow from USD 1.0 billion in 2020 to USD 4.2 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 26.3% during the forecast period.

Various factors such as increasing volume and variety of business data, emerging need for business agility and accessibility, and growing demand for real-time streaming analytics are expected to drive the adoption of the data fabric software and services.

The COVID-19 pandemic has forced businesses to find new alternatives for speedy recovery and attention to the urgent need to access enough data in crisis times. Disparate data stores hamper the efforts of business leaders to make fully informed decisions. Using a modern data architecture approach called data fabric, Ernst & Young (EY) developed Business Resiliency Data Fabric that enables access to data wherever it lives. Data fabric supports rapid technological change while increasing data entropy. To help alleviate the consequences of COVID-19, Denodo launched the Coronavirus Data Portal (CDP), a collaborative initiative that leverages data virtualization to unify critical datasets originally exposed in different formats from multiple sources and countries and make the unified data open to everyone. Using the CDP and the data virtualization capabilities of the Denodo Platform, pmOne created detailed reports and AI analysis, seamlessly orchestrating all the information streams in the pmOne Share Cockpit. The collaboration of Denodo and pmOne provided the global community with trustworthy, up-to-date data about COVID-19 that can be used to develop new intelligence about COVID-19 and reduce its impact.

Banks have transitioned to remote sales and service teams and launched digital outreach to customers to make flexible payment arrangements for loans and mortgages. Grocery stores have shifted to online ordering and delivery as their primary business. Schools in many locales have pivoted to 100% online learning and digital classrooms. Doctors have begun delivering telemedicine, aided by more flexible regulation. These approaches have resulted in the rise of volume and variety of business data, the rise in need for business agility and data accessibility, and increasing demand for real-time streaming analytics, contributing to the growth of the data fabric market.

The software segment to have the largest market size during the forecast period

The data fabric market has been segmented based on components into software and services. Data fabric makes the movement of data between cloud, storage systems, and data centers smoother, with low latency contributing to the adoption of data fabric software. The services segment, on the other hand, has been bifurcated into consulting services, support and maintenance, and education and training services.

In-memory data fabric segment to have the highest CAGR during the forecast period

Based on type of data fabric, the market has been segmented into disk-based data fabric and in-memory data fabric. The adoption of in-memory data fabric is expected to increase significantly in the coming years, owing to the reduction of costs that arise due to the storage and analysis of huge amounts of data.

Fraud detection and security management segment to account for largest market size during the forecast period

The data fabric market, by business application, comprises fraud detection and security management; governance, risk and compliance management; customer experience management; sales and marketing management; business process management; and other applications including supply chain management, asset management, and workforce management. Data fabric helps in automating the detection of data anomalies automatically and trigger actions to counter them. This not only minimizes losses but also improves regulatory compliance leading to the adoption of data fabric software for fraud detection and security management

Among regions, APAC to account for the highest CAGR during the forecast period

North America is expected to hold the largest market size in the global data fabric market. In contrast, APAC is expected to grow at the highest CAGR during the forecast period due to its growing technology adoption rate. The major countries in APAC that are technology-driven and present major opportunities in terms of investments and revenue include Australia, China, Japan, India, and South Korea. This is the major driving factor for the adoption of Data fabric software in APAC.

Key Topics Covered:

1 Introduction

2 Research Methodology

3 Executive Summary

4 Premium Insights
4.1 Attractive Opportunities in the Data Fabric Market
4.2 Market, by Application
4.3 Market, by Region
4.4 North America Market, by Application and Vertical

5 Market Overview
5.1 Market Dynamics
5.1.1 Drivers Increasing Volume and Variety of Business Data Emerging Need for Business Agility and Accessibility Growing Demand for Real-Time Streaming Analytics
5.1.2 Restraints Lack of Awareness About Data Fabric Lack of Integration with Legacy Systems
5.1.3 Opportunities Generating Positive Return on Investment (Roi) Increasing Adoption of Cloud Advancement of In-Memory Computing
5.1.4 Challenges Disinclination Toward Investment in New Technologies Lack of Sufficiently Skilled Workforce
5.2 Industry Trends
5.2.1 Introduction
5.2.2 Data Fabric Market: COVID-19 Impact
5.2.3 Case Study Analysis Use Case 1: Ducati and Netapp Together Build a Data Fabric Solution to Boost Innovation Use Case 2: Bloomreach Used Nexla’s Solution to Enhance the Customer-Centered Data Approach Use Case 3: Ingenico Used HPE Ezmeral Data Fabric Solution to Develop a Single Unified Data Platform Use Case 4: Leading Healthcare Provider Used HPE Ezmeral Data Fabric to Bring Together Disparate Data Sources into One Data Lake Use Case 5: Ymca of Greater Toronto Leveraged a Data Fabric to Rapidly Deliver a Solution That Allowed Members to Safely Return to Their Facilities During COVID-19

6 Data Fabric Market, by Component
6.1 Introduction
6.1.1 Component: Market Drivers
6.1.2 Component: COVID-19 Impact
6.2 Software
6.3 Services
6.3.1 Managed Services
6.3.2 Professional Services Consulting Services Support and Maintenance Education and Training

7 Data Fabric Market Analysis, by Type of Data Fabric
7.1 Introduction
7.1.1 Type of Data Fabric: Market Drivers
7.1.2 Type of Data Fabric: COVID-19 Impact
7.2 Disk-Based Data Fabric
7.3 In-Memory Data Fabric

8 Data Fabric Market Analysis, by Business Application
8.1 Introduction
8.1.1 Business Application: Market Drivers
8.1.2 Business Application: COVID-19 Impact
8.2 Fraud Detection and Security Management
8.3 Governance, Risk, and Compliance Management
8.4 Customer Experience Management
8.5 Sales and Marketing Management
8.6 Business Process Management
8.7 Other Applications

9 Data Fabric Market, by Deployment Mode
9.1 Introduction
9.1.1 Deployment Mode: Market Drivers
9.1.2 Deployment Mode: COVID-19 Impact
9.2 On-Premises
9.3 Cloud

10 Data Fabric Market, by Organization Size
10.1 Introduction
10.1.1 Organization Size: Market Drivers
10.1.2 Organization Size: COVID-19 Impact
10.2 Large Enterprises
10.3 Small and Medium-Sized Enterprises

11 Data Fabric Market, by Vertical
11.1 Introduction
11.1.1 Vertical: Market Drivers
11.1.2 Vertical: COVID-19 Impact
11.2 Data Fabric: Enterprise Use Cases
11.3 Banking, Financial Services, and Insurance
11.4 Telecommunications and It
11.5 Retail and E-Commerce
11.6 Healthcare and Life Sciences
11.7 Manufacturing
11.8 Government
11.9 Energy and Utilities
11.10 Media and Entertainment
11.11 Other Verticals

12 Data Fabric Market, by Region
12.1 Introduction
12.2 North America
12.3 Europe
12.4 Asia-Pacific
12.5 Middle East and Africa
12.6 Latin America

13 Competitive Landscape
13.1 Overview
13.2 Company Evaluation Quadrant
13.2.1 Stars
13.2.2 Emerging Leaders
13.2.3 Pervasive Players
13.2.4 Participants
13.3 Startup/SME Evaluation Quadrant
13.3.1 Progressive Companies
13.3.2 Responsive Companies
13.3.3 Dynamic Companies
13.3.4 Starting Blocks
13.4 Competitive Scenario
13.4.1 Product Launches and Product Enhancements
13.4.2 Deals
13.4.3 Others

14 Company Profiles
14.1 Introduction
14.2 Key Players
14.2.1 IBM
14.2.2 Oracle
14.2.3 Informatica
14.2.4 Talend
14.2.5 Denodo Technologies
14.2.6 SAP
14.2.7 Netapp, Inc.
14.2.8 Software Ag
14.2.9 Splunk, Inc.
14.2.10 HPE
14.2.11 Dell Technologies
14.2.12 Teradata
14.2.13 Precisely
14.2.14 Global IDS
14.2.15 Tibco Software
14.2.16 Idera
14.3 Start-Up/SME Profiles
14.3.1 Nexla
14.3.2 Stardog
14.3.3 Gluent
14.3.4 Starburst Data
14.3.5 Hexstream
14.3.6 Qomplx
14.3.7 Cluedin
14.3.8 Iguazio
14.3.9 Cinchy

15 Appendix

For more information about this report visit

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