What is
Data Fabric?
End-to-end data management design
Definition
Data Fabric is an end-to-end data management design that supports the integration of various and heterogenous data pipelines, services, and environments using automation.
It supports a combination of different data integration styles and leverage active metadata, knowledge graphs, semantics and ML to augment data integration design and delivery.
The primary goal of a Data Fabric is to support flexible, agile, and timely data management for modern applications and analytics, regardless of where data resides or how it is structured.
Benefits of Data Fabric
Share data across organization
Solve complex data problems
Manage data regardless of where data is stored
Seamless access and data sharing in distributed data environment
Greater flexibility, scalability, and efficiency in data management
Better insights and decision-making
Do I need to shift from Data Fabric to Data Mesh?
The hype about Data Mesh continues to grow, and innovative companies seek to implement the approach to their data management systems. One might ask the question: What about the data architecture we already have in place? Do we need to say goodbye to Data Fabric now? As Gartner® states in the Hype Cycle for Data Management 2023: “Several technologies and disciplines around future data architectures are currently heading into or passing through the trough: DataOps, data fabric, active metadata management, and augmented data cataloging/metadata management solutions”—stating that database features are moving towards “obsolete before plateau”. But this doesn’t mean that Data Fabric is less functional today.
Gartner® rather assumes that the functions of Data Fabric will converge with Data Mesh. The objective is the same: Greater access and use of more of the company’s data.
While one might believe Data Mesh and Data Fabric are opposing approaches, they ultimately pursue the same goal of improving data management. Data Mesh focuses on decentralized responsibility and collaboration, whereas Data Fabric focuses on a unified infrastructure and data integration.
Data Mesh vs. Data Fabric
Data Mesh and Data Fabric are both concepts designed to address challenges in the modern data landscape, particularly as organizations grow in complexity and scale. While they share some overlapping principles, they are distinct in their approach and focus.
Whether you choose Data Fabric, Data Mesh, or a blend of both will depend on your specific needs and requirements—and the considerations for the architectures and technologies you already have in place. Data Mesh is about rethinking organizational structures and responsibilities around data, while Data Fabric is about creating a unified technological layer for data access and integration.
