Data Fabric Market Size, Share, Opportunities, And Trends By Deployment (Cloud, On-Premise), By Type (Disk–based, In–Memory), By Application (Fraud Detection And Security Management, Government, Risk And Compliance Management, Customer Experience Management, Others), By Industry Vertical (Healthcare And Lifesciences, BFSI, IT And Telecom, Retail And E-commerce, Others), And By Geography - Forecasts From 2024 To 2029

  • Published : Mar 2024
  • Report Code : KSI061616851
  • Pages : 141

The data fabric market is projected to show steady growth during the forecast period.

Data fabric refers to a centralized data framework that integrates data assets, databases, and architectures across an organization. It represents a novel approach to data management, employing a network-based architecture rather than relying on point-to-point connections. The versatility of data fabric allows it to serve various purposes, such as collecting distributed data for an application or extending its reach to encompass all enterprise data.

Data fabric is a conceptual layer that creates links between data across different systems, leading to a unified viewpoint. It assists organizations in addressing complex data issues and implementing practical scenarios by effectively overseeing data across a range of applications, platforms, and geographic locations. Increased data volume complexity, hybrid and multi-cloud implementation, and changing analytical landscape are driving the data fabric market growth.

Market Drivers

  • Increased data volume complexity boosts data fabric market growth

The rapid expansion of data in various formats, including structured, unstructured, and semi-structured, originating from multiple sources such as cloud storage, on-premise servers, and IoT devices, presents a significant challenge in terms of effective management and accessibility.

The surge of data requires the implementation of data fabrics, which act as a unified solution for handling, merging, and overseeing data in various settings. By eliminating data silos, data fabrics streamline the retrieval and utilization of essential information, irrespective of its origin or structure. This centralized authority boosts the effectiveness of data management and equips organizations with a thorough insight into their significant data resources.

  • Hybrid and Multi-Cloud Implementation drives data fabric market growth.

The emergence of hybrid and multi-cloud deployments is a significant factor driving the adoption of data fabrics. Numerous companies utilize a combination of cloud services and on-premise infrastructure, leading to a fragmented data landscape with information spread across different locations. Data fabrics address this challenge by offering a centralized platform.

The centralized strategy streamlines data governance, ensuring uniform policies and access controls across all environments. Additionally, data fabrics eliminate data silos by enabling seamless data movement and integration between these diverse locations. This enables organizations to fully harness the potential of the data, promoting a cohesive and data-centric approach throughout the entire organization.

For instance, in 2023, IBM unveiled the IBM Hybrid Cloud Mesh, an innovative solution aimed at empowering businesses. This cutting-edge SaaS offering streamlines application connectivity across diverse cloud environments, on-premise infrastructure, and edge locations.

  • Changing analytical landscape propels data fabric market growth

As analytics technology advances, the significance of data fabrics is growing. Sophisticated analytics and AI applications demand a continuous flow of data from various origins. Training an AI model to forecast equipment breakdowns in a manufacturing plant. The model would require information from sensor readings, maintenance records, and past failure trends - which may be stored in different formats and locations.

Data fabrics serve as a connection point, facilitating smooth data integration. They eliminate data silos and ensure that all relevant data sets are easily accessible for analysis. This unified data infrastructure is essential for supporting advanced analytics and AI projects. By granting effortless access to a comprehensive data landscape, data fabrics empower businesses to uncover deeper insights and make informed, data-driven choices with increased certainty.

The North American data fabric market is anticipated to grow significantly

North America is projected to grow in the data fabric market for favorable reasons. To begin with, companies in North America are struggling with an overwhelming amount of data. The rapid expansion of data in various formats and from different sources such as the cloud, on-premise, and IoT presents significant management challenges. Data fabrics offer a centralized approach to effectively manage and integrate the data, which is particularly appealing to organizations seeking solutions for data extension. Additionally, North American enterprises are at the forefront of hybrid and multi-cloud adoption. Data fabrics serve as a central platform for managing data across complex environments, streamlining data governance, and promoting a cohesive data landscape.

Market Restraints

  • Complications in implementing data fabric slow down the data fabric market growth.

Implementing data fabrics can be a challenging task as it involves integrating them with the existing data infrastructure and processes. This often necessitates the involvement of specialized experts and a substantial upfront investment in planning, configuration, and training.

  • The evolving landscape of data fabric hinders the data fabric market growth.

The data fabric market continues to develop, and there remains a lack of comprehensive standardization among various vendors' offerings. This disparity can pose difficulties for organizations when it comes to comparing solutions and achieving smooth integration.

Key Developments

  • March 2024: NTT DATA, a prominent leader in digital business and IT has formed a collaborative alliance with Promethium, an innovator in data fabric technology. The primary objective of this strategic partnership is to expedite the implementation of Promethium's AI-driven data fabric throughout North America.
  • February 2024: LigaData introduced its latest breakthroughs at MWC Barcelona LigaData Telecom Data Fabric 4.0 and Telecom AI Applications. These advancements enable telecommunications operators to evolve into data-centric technology enterprises, enhancing their revenue, customer experience, and market presence.
  • May 2023: Microsoft Fabric is a robust data analytics platform designed for the AI era. It combines data integration, governance, and analytics tools, allowing businesses of all sizes to harness the power of their data. Fabric facilitates collaboration between data teams and business users, encouraging data-driven decision-making.

Company Products

  • HP Ezmeral Data Fabric Software: HPE Ezmeral Data Fabric Software serves as a protected data center for hybrid and multi-cloud setup. It offers file storage, object storage, NoSQL databases, and event streams, all conveniently accessible from one central location. This streamlines data administration, analysis, and support for AI tasks throughout the enterprise.
  • Tibco EBX: offered by Tibco Software, it provides a comprehensive software solution designed to handle master data, reference data, and metadata efficiently. It presents a user-friendly interface for the creation, management, and distribution of the essential data throughout organization.

Segmentation

  • By Deployment
    • Cloud
    • On-Premise
  • By Type
    • Disk–based
    • In–Memory
  • By Application
    • Fraud Detection and Security Management
    • Government
    • Risk and Compliance Management
    • Customer Experience Management
    • Others
  • By Industry Vertical
    • Healthcare and Lifesciences
    • BFSI
    • IT and Telecom
    • Retail and E-commerce
    • Others
  • By Geography
    • North America
      • United States
      • Canada
      • Mexico
    • South America
      • Brazil
      • Argentina
      • Others
    • Europe
      • United Kingdom
      • Germany
      • France
      • Italy
      • Spain
      • Others
    • Middle East and Africa
      • Saudi Arabia
      • UAE
      • Others
    • Asia Pacific
      • Japan
      • China
      • India
      • South Korea
      • Taiwan
      • Thailand
      • Indonesia
      • Others

1. INTRODUCTION

1.1. Market Overview

1.2. Market Definition

1.3. Scope of the Study

1.4. Market Segmentation

1.5. Currency

1.6. Assumptions

1.7. Base and Forecast Years Timeline

1.8. Key Benefits to the Stakeholder

2. RESEARCH METHODOLOGY  

2.1. Research Design

2.2. Research Processes

3. EXECUTIVE SUMMARY

3.1. Key Findings

3.2. Analyst View

4. MARKET DYNAMICS

4.1. Market Drivers

4.2. Market Restraints

4.3. Porter’s Five Forces Analysis

4.3.1. Bargaining Power of Suppliers

4.3.2. Bargaining Power of Buyers

4.3.3. Threat of New Entrants

4.3.4. Threat of Substitutes

4.3.5. Competitive Rivalry in the Industry

4.4. Industry Value Chain Analysis

4.5. Analyst View

5. DATA FABRIC MARKET BY DEPLOYMENT

5.1. Introduction

5.2. Cloud

5.2.1. Market Trends and Opportunities

5.2.2. Growth Prospects

5.2.3. Geographic Lucrativeness

5.3. On-Premise

5.3.1. Market Trends and Opportunities

5.3.2. Growth Prospects

5.3.3. Geographic Lucrativeness

6. DATA FABRIC MARKET BY TYPE

6.1. Introduction

6.2. Disk-Based

6.2.1. Market Trends and Opportunities

6.2.2. Growth Prospects

6.2.3. Geographic Lucrativeness

6.3. In-Memory

6.3.1. Market Trends and Opportunities

6.3.2. Growth Prospects

6.3.3. Geographic Lucrativeness

7. DATA FABRIC MARKET BY APPLICATION 

7.1. Introduction

7.2. Fraud Detection and Security Management

7.2.1. Market Trends and Opportunities

7.2.2. Growth Prospects

7.2.3. Geographic Lucrativeness

7.3. Government

7.3.1. Market Trends and Opportunities

7.3.2. Growth Prospects

7.3.3. Geographic Lucrativeness

7.4. Risk and Compliance Management

7.4.1. Market Trends and Opportunities

7.4.2. Growth Prospects

7.4.3. Geographic Lucrativeness

7.5. Customer Experience Management 

7.5.1. Market Trends and Opportunities

7.5.2. Growth Prospects

7.5.3. Geographic Lucrativeness

7.6. Others

7.6.1. Market Trends and Opportunities

7.6.2. Growth Prospects

7.6.3. Geographic Lucrativeness

8. DATA FABRIC MARKET BY INDUSTRY VERTICAL

8.1. Introduction

8.2. Healthcare and Lifesciences 

8.2.1. Market Trends and Opportunities

8.2.2. Growth Prospects

8.2.3. Geographic Lucrativeness

8.3. BFSI

8.3.1. Market Trends and Opportunities

8.3.2. Growth Prospects

8.3.3. Geographic Lucrativeness

8.4. IT and Telecom

8.4.1. Market Trends and Opportunities

8.4.2. Growth Prospects

8.4.3. Geographic Lucrativeness

8.5. Retail and E-Commerce

8.5.1. Market Trends and Opportunities

8.5.2. Growth Prospects

8.5.3. Geographic Lucrativeness

8.6. Others

8.6.1. Market Trends and Opportunities

8.6.2. Growth Prospects

8.6.3. Geographic Lucrativeness

9. DATA FABRIC MARKET BY GEOGRAPHY

9.1. Introduction

9.2. North America

9.2.1. By Deployment

9.2.2. By Type 

9.2.3. By Application  

9.2.4. By Industry Vertical

9.2.5. By Country

9.2.5.1. United States

9.2.5.1.1. Market Trends and Opportunities

9.2.5.1.2. Growth Prospects

9.2.5.2. Canada

9.2.5.2.1. Market Trends and Opportunities

9.2.5.2.2. Growth Prospects

9.2.5.3. Mexico

9.2.5.3.1. Market Trends and Opportunities

9.2.5.3.2. Growth Prospects

9.3. South America

9.3.1. By Deployment

9.3.2. By Type 

9.3.3. By Application  

9.3.4. By Industry Vertical

9.3.5. By Country

9.3.5.1. Brazil

9.3.5.1.1.1. Market Trends and Opportunities

9.3.5.1.1.2. Growth Prospects

9.3.5.2. Argentina

9.3.5.2.1.1. Market Trends and Opportunities

9.3.5.2.1.2. Growth Prospects

9.3.5.3. Others

9.3.5.3.1.1. Market Trends and Opportunities

9.3.5.3.1.2. Growth Prospects

9.4. Europe

9.4.1. By Deployment

9.4.2. By Type 

9.4.3. By Application  

9.4.4. By Industry Vertical

9.4.5. By Country

9.4.5.1. United Kingdom

9.4.5.1.1. Market Trends and Opportunities

9.4.5.1.2. Growth Prospects

9.4.5.2. Germany

9.4.5.2.1. Market Trends and Opportunities

9.4.5.2.2. Growth Prospects

9.4.5.3. France

9.4.5.3.1. Market Trends and Opportunities

9.4.5.3.2. Growth Prospects

9.4.5.4. Italy

9.4.5.4.1. Market Trends and Opportunities

9.4.5.4.2. Growth Prospects

9.4.5.5. Spain

9.4.5.5.1. Market Trends and Opportunities

9.4.5.5.2. Growth Prospects

9.4.5.6. Others

9.4.5.6.1. Market Trends and Opportunities

9.4.5.6.2. Growth Prospects

9.5. Middle East and Africa

9.5.1. By Deployment

9.5.2. By Type 

9.5.3. By Application  

9.5.4. By Industry Vertical

9.5.5. By Country

9.5.5.1. Saudi Arabia

9.5.5.1.1. Market Trends and Opportunities

9.5.5.1.2. Growth Prospects

9.5.5.2. UAE

9.5.5.2.1. Market Trends and Opportunities

9.5.5.2.2. Growth Prospects

9.5.5.3. Others

9.5.5.3.1. Market Trends and Opportunities

9.5.5.3.2. Growth Prospects

9.6. Asia Pacific

9.6.1. By Deployment

9.6.2. By Type 

9.6.3. By Application  

9.6.4. By Industry Vertical

9.6.5. By Country

9.6.5.1. Japan

9.6.5.1.1. Market Trends and Opportunities

9.6.5.1.2. Growth Prospects

9.6.5.2. China

9.6.5.2.1. Market Trends and Opportunities

9.6.5.2.2. Growth Prospects

9.6.5.3. India

9.6.5.3.1. Market Trends and Opportunities

9.6.5.3.2. Growth Prospects

9.6.5.4. South Korea

9.6.5.4.1. Market Trends and Opportunities

9.6.5.4.2. Growth Prospects

9.6.5.5. Taiwan

9.6.5.5.1. Market Trends and Opportunities

9.6.5.5.2. Growth Prospects

9.6.5.6. Thailand

9.6.5.6.1. Market Trends and Opportunities

9.6.5.6.2. Growth Prospects

9.6.5.7. Indonesia

9.6.5.7.1. Market Trends and Opportunities

9.6.5.7.2. Growth Prospects

9.6.5.8. Others

9.6.5.8.1. Market Trends and Opportunities

9.6.5.8.2. Growth Prospects

10. COMPETITIVE ENVIRONMENT AND ANALYSIS

10.1. Major Players and Strategy Analysis

10.2. Market Share Analysis

10.3. Mergers, Acquisitions, Agreements, and Collaborations

10.4. Competitive Dashboard

11. COMPANY PROFILES

11.1. Hewlett Packard Enterprise Development LP

11.2. TIBCO Software Inc.

11.3. Talend, Inc.

11.4. Cloudera

11.5. SAP SE

11.6. Oracle

11.7. IBM

11.8. NetApp, Inc.

11.9. CluedIn

11.10. Dell Technologies Inc.


Hewlett Packard Enterprise Development LP

TIBCO Software Inc.

Talend, Inc.

Cloudera

SAP SE

Oracle

IBM

NetApp, Inc.

CluedIn

Dell Technologies Inc.