Data Fabric Market Size, Share, Growth Analysis, By Component(Solutions, Services [Professional Services (Consulting, Education and Training, Support and Maintenance)), By Type(Disk-Based, In-Memory), By Organization Size(Large Enterprises, Small and Medium-Sized Enterprises), By Deployment Mode(On-Premises, Cloud), By Application(Fraud Detection & Security Management, Governance, Risk & Compliance Management, Customer Intelligence), By Vertical(BFSI, Government, Defense, & Public Agencies), By Region - Industry Forecast 2025-2032

Data Fabric Market size was valued at USD 2.23 Billion in 2023 and is poised to grow from USD 2.92 Billion in 2024 to USD 25.3 Billion by 2032, growing at a CAGR of 31% during the forecast period (2025-2032).

The widespread use of the internet and the number of connected devices such as smartphones, laptops, tablets and PCs access the amount and types of corporate data such as, sensors and cameras. The use of data analytics by businesses is driven by the increasing demand for exploratory data analytics, and the collection of data from the data fabric for analytical purposes. 

The proliferation of online platforms and the digital revolution have accelerated the processing of data. Companies protect data and knowledge from a variety of remote locations. Thus, enabling rapid access to data in remote environments creates a wealth of information for data management providers. The richness and diversity of business data assets increases the complexity of data governance and data integration, thereby facilitating the adoption of data fabrics within organizations. 

Recently, big data analytics has attracted a lot of attention from practitioners and researchers. Companies are predicted to build data fabrics to power enterprise-wide data and analytics and automate many tasks related to data discovery, integration, manipulation and preparation. Global investments in big data analytics from private and public sources have reached $100,000. The demand for big data analytics technologies is driven by the rapidly increasing volume and complexity of data due to increased cloud computing and mobile data traffic, and the development and adoption of technologies such as Artificial Intelligence (AI) and Internet of Things (IoT).