In our last blog in this series, we took a deeper dive into the components that make up a Data Fabric and Data Mesh. If you look closely, the first thing that may have jumped out is that there’s significant overlap between the two lists. Here’s a quick recap. Both a Data Fabric and a Data Mesh require the following:
The Data Fabric and Data Mesh: complementary approaches
So, as we alluded to in the second part of this blog series, maybe a Data Fabric is NOT a competing approach to a Data Mesh. Or rather, it does NOT have to be. What if a Data Fabric is actually complementary to a Data Mesh? What if having a Data Fabric implemented first accelerates the implementation of a Data Mesh, should it be needed later on?
In this blog, we’ll discuss how a Data Fabric actually supports building a Data Mesh because the Fabric provides the underlying data management and integration framework that enables the Data Mesh’s core principles to function effectively.
To recap what we discussed in Part 2 of this series, here’s how a Data Fabric contributes to building a Data Mesh:
In short, a Data Fabric is highly relevant to building a Data Mesh, as it provides the necessary data management and integration capabilities to support the Data Mesh’s core principles. Leveraging a Data Fabric enables organizations to create and deploy a robust, scalable, highly efficient data infrastructure, enabling domain teams to work independently while still benefiting from shared data resources and insights.
Creating a comprehensive data infrastructure
Wait…so.. I can have both?
Yes.. but only IF you NEED both.
It’s important to reiterate that Data Mesh and Data Fabric are not competing paradigms but actually complement one another. While each addresses different aspects of data management and integration, combined they can create a truly comprehensive and effective data infrastructure.
The main goal of Data Mesh is to enable better collaboration, data ownership, and data sharing across different domain teams in large-scale organizations. To achieve those goals, a Data Mesh focuses on the organizational and architectural aspects of managing data at scale, promoting decentralization, domain-oriented architecture, data as a product, and self-serve data platform capabilities.
On the other hand, a Data Fabric provides a unified and consistent view of data, making it easier for users to access, analyze, and use data across the organization. It focuses on addresses the challenges of data access, integration, and management across disparate sources
When you implement a Data Fabric first, having a Data Mesh becomes instantly easier and a natural add on. At the end of the day, the Data Fabric and Data Mesh can complement each other in the following ways:
To conclude, the Data Mesh and Data Fabric are complementary concepts. As individual entities they offer unique qualities, the Data Mesh focusing on the organizational and architectural aspects, while the Data Fabric provides the underlying technological framework for effective data management and integration. Combined they can create a robust and efficient data infrastructure. By leveraging both paradigms, organizations can build a comprehensive data infrastructure that promotes collaboration, data ownership, and efficient data sharing across domains.
My take?
Implementing a Data Fabric product can be done in a fraction of the time, less than a day in most cases, than it typically takes to implement a Data Mesh. A Data Fabric can deliver value in the first week. But a Data Mesh can take 18+ months to implement and truly deliver value.
So, why not start with the Data Fabric first to see how the challenges around discovery, access, self-service, and security can be solved? Then, if your organization still requires the benefits of the Data Mesh, you can simply add to the Data Fabric as opposed to investing often millions of dollars and waiting for over a year hoping to see value.
To arrange a demonstration of Promethium’s Data Fabric product click here.
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