Data Virtualization vs. Data Fabric: What are the Differences?

Today's data environment is becoming increasingly complex, and enterprises need to be able to quickly access and integrate data from various different formats and sources. To meet this demand, many data integration technologies have emerged, including Data Virtualization and Data Fabric. Although both can provide solutions for data integration, there are some key differences between them. This article will explore what sets Data Virtualization apart from Data Fabric.

Data Virtualization

Data Virtualization is an enterprise integration technology that distributes data across different systems. It provides a unified data view through a virtual layer and can integrate data into multiple applications. Data Virtualization technology abstracts different data sources, allowing enterprises to easily access data without worrying about where it is stored. Using Data Virtualization technology can also increase data availability and integrity since data is integrated into a single view.

Data Fabric

Data Fabric is an enterprise integration technology that also distributes data across different systems, but it places more emphasis on the overall structure of data. Data Fabric technology allows enterprises to move and manage data freely between different data sources. It can provide a unified data management platform for enterprises, thereby increasing data availability and reliability. Using Data Fabric technology can also increase enterprise control over data and enhance data security.

Differences between Data Virtualization and Data Fabric

Data Virtualization is a transparent way of integrating distributed data. It typically integrates multiple data sources (such as relational databases, NoSQL databases, web services, and other data sources) into a virtual database, allowing users to access data from all data sources through a single interface. This provides a unified way of accessing data, reduces the need for data replication and synchronization, and improves the efficiency of data integration.

Data Fabric is a more comprehensive architectural model that aims to achieve an overall structure for enterprise data. Data Fabric usually refers to a unified data structure that can integrate different data sources and provide users with a unified data access interface. The goal of Data Fabric is to provide an overall data structure that makes it easier for enterprises to manage and control data, as well as to facilitate data analysis and application development.

In short, Data Virtualization focuses more on data integration technology, with a focus on achieving transparent integration of distributed data; while Data Fabric focuses more on data integration architecture, with a focus on achieving an overall structure for enterprise data that makes it easier for enterprises to manage and control data.

Implementing Data Fabric with Canner Enterprise

Data Virtualization technology and Data Fabric architectual concept are important innovation for modern enterprises in data integration. Canner Enterprise designs highly scalable and supportive Data Virtualization technology to assist enterprises in implementing Data Fabric architecture.

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