Using Elastic as a global data mesh: Unify data access with security, governance, and policy

We should probably start with what it’s not. A “data mesh” is not the same as a “data fabric.” A data fabric allows data flowing in from across the enterprise (from the edge, the network, the applications, the appliances . . . literally everywhere) to be confidently received and persisted, making it available for delivery to any consumers who might want to ingest that data. That’s really the important part: While some data fabric tools provide the ability to perform low-level data manipulation and logic-based routing, the data fabric cannot actually do anything with the data received except deliver it.

By contrast, a data mesh makes the data collected from across the entire network available to be retrieved and analyzed at any or all points of the ecosystem — as long as the user has permissions to access it. A data mesh provides a unified yet distributed layer that simplifies and standardizes data operations, such as search and retrieval, aggregations, correlation, analysis, and delivery. A data mesh creates a data product that other services and business operations can use to get faster, more comprehensive answers to base their decisions on. 

So, perhaps a more concise way to define the difference is in the usability of the data: a data fabric delivers raw or semi-processed data; the data mesh lets you actually use it.

If there’s any hope for the data mesh to become more than a concept or marketing term, it has to deliver on a defined set of criteria that addresses valid business needs and provides solid value while doing it. To that end, let’s make the “data mesh” buzzword a little more real and practical.