DATA FABRIC VS DATA MESH: AN APPLES & ORANGES STORY?
Data fabric and data mesh are two concepts that have gained a lot of attention in the world of data management. While they share some similarities, they have some fundamental differences that are important to understand. In this article, we will explain the difference between data fabric vs data mesh.
What is a Data Fabric?
A data fabric is an architecture that provides a unified and consistent view of an organization’s data, regardless of where it resides, how it’s stored, or how it’s accessed. It allows data to flow seamlessly between different systems and applications, while maintaining data integrity, security, and governance. It provides a way to seamlessly integrate and access data from different systems, applications, databases, and clouds, making it easier for organizations to derive insights and make decisions.
What is a Data Mesh?
A data mesh is a decentralized approach to data management that empowers teams to own and manage their own data domains. It recognizes that data is a product and treats it as such, with individual teams responsible for their own data products. The goal of a data mesh is to enable faster and more efficient data delivery by allowing teams to work independently and iterate quickly.
Difference between Data Fabric and Data Mesh
The fundamental difference between data fabric and data mesh is in their approach to data management. A data fabric is a centralized approach, while a data mesh is a decentralized approach. A data fabric provides a unified and consistent view of an organization’s data, while a data mesh enables teams to own and manage their own data domains.
Another key difference between data fabric vs data mesh is in their focus. A data fabric focuses on providing a seamless and consistent view of data across an organization, while a data mesh focuses on empowering teams to own and manage their own data domains. A data mesh typically creates more room for innovation.
Conclusion
In conclusion, while data fabric and data mesh share some similarities, they have fundamental differences in their approach to data management. A data fabric is a centralized approach that provides a unified and consistent view of an organization’s data, while a data mesh is a decentralized approach that empowers teams to own and manage their own data domains. Both approaches have their own advantages and disadvantages, and the choice between the two will depend on the specific needs of the organization.
It is worth noting that choosing between data mesh and fabric is not always a binary decision. Some parts of an organization may choose to implement data mesh, while others may prefer the data fabric approach.