What is a data fabric? This is a question that is being asked more frequently as enterprises seek to do a better job of managing and analyzing data. Data fabric is a term used to describe an architectural approach that enables enterprises to manage and process data across multiple platforms and clouds. Is it similar to or different from a data mesh? When should enterprises use a data fabric? What are the benefits of using data fabric in edge computing? These critical questions need answers before deciding whether to deploy a data fabric.
Defining the enterprise data fabric
A data fabric is a metadata-driven architectural approach that enables an organization to collect, process, and analyze data from disparate sources in real-time. With a data fabric applied virtually atop various data repositories, data fabrics provide a unified view of data, regardless of location. Organizations can now bring siloed data together for analysis and reporting. However, it’s essential to remember that while the management is unified, the storage is not.
How is data fabric similar to or different from a data mesh?
Like a data mesh, a data fabric aims to address many of the same issues. For instance, both approaches address the problem of managing data in a diverse data environment. However, both use different strategies to accomplish this task. The data fabric strives to construct a single virtual management layer atop distributed data. In contrast, the data mesh aims to provide distributed teams with a method for managing data according to their own needs while still adhering to common governance standards.
When should enterprises use a data fabric?
There are many reasons an organization might opt to use a data fabric. Sometimes, it may be because the organization has outgrown its current data management infrastructure. Additionally, an enterprise might deploy a data fabric to improve its ability to analyze data from disparate sources. Or if it needs to provide better access to data for distributed teams.
What are/are there data fabric use cases in edge computing?
One data fabric use case helps with the typical problem of getting data back to the core efficiently and securely. The goal is to retrieve data from numerous edge data centers and send it to the core data center with minimal latency. A data fabric can create a simple solution for this by using its transport capabilities to embed messages into a message stream at the edge. The data fabric can then handle all data motion from edge to core, including security while in motion and at rest.
As the message stream contains information on the data center name, source machine name, sensor name, or event type, all edge center data may combine into a single message stream. Companies may nonetheless analyze each subset of the data separately.
Edge and data fabric are intertwined
Edge computing is predicated on the idea that more data is being created by devices, be they cameras or sensors in a factory. Technologies and architectures, such as data fabric and data mesh, that help manage and make sense of data are an important piece of the edge ecosystem.
data fabric | data mesh | edge computing | observability | use case