The concept of data fabric is emerging as an approach to assist organizations to deal more effectively with fast growing data. It enables tools and applications to access data via various interfaces including Apache KAFKA, Open Database Connectivity, Hadoop Distributed File System, Representative State Transfer, Portable Operating System Interface, and Network File System. The term takes reference from technologies designed to create converged platforms that support disparate data management, analysis, processing, and storage. Let’s find out more about data fabric:
What Issues does Data Fabric Address?
- Availability and reliability: When a problem arises, the data fabric must provide an environment that is highly reliable, heals itself, and manages itself. This way, it can ensure high availability to service mission critical needs.
- Unified data environments: A global namespace can make files easier to access and locate, supporting multi-site computing environments, support application development, take a snapshot of the data for backups, enable compression to help reduce overall storage requirements, as well as provide strong levels of security.
- Multi-site support: Allows users to access data from systems running along the edge of the network, in cloud computing environments and the enterprise data center
- Reliability, speed, and scalability: Access points leading to data—maintained within the data fabric—must meet business requirements pertaining to reliability, scale, and speed without requiring trade-offs.
- Data compilation from established systems: Should happen regardless of future requirement and size for scalability. Data to be made available to all applications.
Why is Unification Potentially Problematic?
The unification of data can be quite a problem because it is stored in many places and formats. Getting said data to the appropriate application in the right way and at the right time is not always an easy problem to address.
What’s more, more work is increasingly done at the edge of the network. Employees and their customers now have applications that access data from various endpoints including smartphones, PCs, laptops, and other options driven by the Internet of Things (IoT).
Organizations are encouraged to move their data into a data fabric in order to meet the needs for an agile and flexible, global data environment. This way, they can efficiently process data generated at the edge. Experts have predicted that servers based upon newer microprocessor architectures such as NVIDA and ARM may become more prevalent in the near future.
Should You Care About Data Fabric?
More businesses are facing significant challenges today, which is one of the reasons why the data fabric concept has become important to major enterprises today. Commercial IT systems are becoming more complex than ever before. Business owners need to work seamlessly across intricate disparate environments and support any existing applications—includes microservice-based types—at the same time.
In the past, each app development team had the option of choosing their approach to retrieving and storing data. That’s why you would find data stored in Big Data repositories, non-relational (NoSQL) databases, relational (SQL) databases, and flat files. However, distributing data into separate silos may not be a viable solution in the future.
That’s where the data fabric comes into the picture. It can offer IT teams many opportunities to address the business requirements to unify data, as well as accelerate and simplify today’s complex computing problems.