Learn the differences between data mesh, and data fabric
data mesh vs data fabric comparison
Data mesh is an approach to building and managing data systems that focuses on creating a decentralized, self-serve data infrastructure. With data mesh, teams are responsible for the data they produce, and they are empowered to build and maintain their own data systems. Data mesh encourages the creation of small, focused data products that can be easily shared and reused across the organization.
Data fabric is a term used to describe a data management architecture that is flexible and scalable, and that allows data to be easily shared and accessed across the organization. A data fabric typically includes a variety of data storage and processing technologies, such as data lakes, data warehouses, and data pipelines, and it may also include tools for data governance and security.
Here is a comparison matrix between data mesh and data fabric:
| Data Mesh | Data Fabric | |
|---|---|---|
| Data Storage | Decentralized | Flexible, can be centralized or decentralized |
| Data Ownership | Decentralized, teams own and are responsible for their data | Can vary, depending on the design of the data fabric |
| Data Access | Self-service access | Can be self-service or require IT involvement |
| Data Quality | Emphasizes data quality and governance | Emphasizes data quality and governance |
| Data Reuse | Encourages creation of small, reusable data products | Encourages data reuse |
One way to think about the difference between data mesh and data fabric is that data mesh is more focused on the process of building and managing data systems, while data fabric is more focused on the infrastructure that supports those systems. Data mesh emphasizes decentralization and self-service, while data fabric can be more flexible in terms of its design and can include a wide range of data storage and processing technologies.