Data Fabric vs. Data Virtualization: What’s the Difference?

Data virtualization and data fabric are two architectures leveraged by data-driven organizations to derive value from data rapidly and support new business requirements like integrated and real-time insights. Data virtualization produces a data abstraction layer by gathering, connecting, and altering data silos to support real-time insights. As such, it offers you direct access to operational and transactional systems in real-time, whether in cloud environments or on-premises.

On the other hand, data fabric helps organizations manage and obtain insights from massive amounts of data. This data is located in different locations, comes in different data types, and is maintained on different databases. Data fabric offers a unified, consistent user experience and access to data for all organization members, making it ideal for geographically diverse organizations with many data sources. Below are some insights into the difference between both data architectures.

Use Cases


Many of the key differences between data fabric architecture and data virtualization revolve around the use cases and data management capabilities provided by the fabric. Data virtualization is usually deployed for reporting, business intelligence, visualization, and ad hoc queries across distributed data. On the other hand, data fabric use cases include IoT analytics, data science, real-time analytics, global analytics, fraud detection, and customer 360.

Suppose you’re an organization that handles large volumes of data. In that case, it undoubtedly makes sense to invest in data virtualization or data fabric solutions to help you manage your data, depending on your unique needs. Innovative software companies such as TIBCO will come in handy when seeking data virtualization and data fabric solutions for your company.

TIBCO is an enterprise-level software brand with a strong focus on data visualization, data science, and predictive analysis. They’re primarily interested in unleashing the potential of real-time data to make quicker and smarter evidence-based decisions. TIBCO also offers software for organizations considering data fabric vs. data virtualization solutions for their unique business needs. Organizations have data in many silos spread across big data lakes, operational data stores, the cloud, traditional data warehouses, and many more.

However, the scattered nature of this data creates several challenges for business teams. As such, data virtualization breaks down your data silos, offering a single place to combine, access, and provision all your data.

Similarly, TIBCO’s data fabric solution helps you unify your data with modern and agile architecture, helping you manage your data despite multiple data sources, silos, and constant change. As such, you can automate, simplify, and accelerate your data pipelines with optimized integration and data management capabilities.

In addition, TIBCO provides low-cost software licenses to the next generation of data analysts and college students. This way, college students can learn about the latest software being utilized in the workforce, preparing them for their future careers. Furthermore, they’re a recognized industry leader in the data science software products sector, providing innovative software solutions to clients for several years.

Investment Necessary to Get Started

Data virtualization is typically an affordable integration solution requiring low-cost investments, especially if you have a simple need like transforming a few data sources to deliver real-time insights. On the other hand, organizations that leverage data fabric see a significantly longer return on investment (ROI) compared to data virtualization.


Data virtualization is often the quickest way to integrate disparate data sources, whether on-premises or cloud. It offers many connectors to different data sources and can organize data for reports, dashboards, and visualization. Conversely, success with data fabric demands more elaborate planning. Therefore, you need a team of developers, business analysts, data architects, data security professionals, among others.

In summary, data fabric and data virtualization are two data architectures used by organizations to manage their data. The points above are some key differences between these two forms of data architecture.