Table of contents
1.
Introduction 
1.1.
Data virtualization
1.2.
Data federation
2.
Data Virtualization vs Data Federation
2.1.
Comparison chart
3.
FAQs
3.1.
What are the advantages of data virtualization?
3.2.
What are the disadvantages of data virtualization?
3.3.
How is data stored in a database federation?
3.4.
What is meant by sharding?
4.
Conclusion 
Last Updated: Mar 27, 2024
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Data Virtualization vs Data Federation

Author Shivam Verma
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Introduction 

Before knowing the difference between Data virtualization and Data federation, we have to understand what Data virtualization and Data federation is?

Data virtualization

Data virtualization is a logical data layer that integrates enterprise data scattered across various systems, manages the unified data for centralized security and governance, and provides it in real-time to business users.

Data federation

Data federation is a technique of collecting, storing and using data that uses virtualization instead of a dedicated database. Data federation, also known as data virtualization, is a method to keep pace with data while still converting it into useful intelligence.

Data Virtualization vs Data Federation

Data virtualization and Data federation are often used interchangeably, which is an error. A type of data virtualization is data federation.

Both data virtualization and data federation are data integration techniques designed to make data easier to access for front-end applications. The difference is that Data federation is a term that refers to techniques that are similar to virtual databases with strict data models. Data virtualization is a concept that refers to services that don't enforce a data model and instead rely on applications to understand the information. This is appropriate for modern applications that aren't as concerned about precision data types like text length.

Comparison chart

FAQs

What are the advantages of data virtualization?

Some of the advantages of data virtualization:

  • Users have easy access to data regardless of where it is stored on the server.
  • Customer happiness improves when access is made easier.
  • Better data security is a result of security policies.
  • Data replication is eliminated, resulting in cost savings.
  • User-friendly interfaces for customized views.
     

What are the disadvantages of data virtualization?

Some of the disadvantages of data virtualization:

  • Third-party providers can maintain availability, which can lead to concerns with availability.
  • The usage of third-party providers may lead to the emergence of security risks.
  • There may be concerns with availability and scalability.
     

How is data stored in a database federation?

Data federation is a type of data virtualization in which data stored in a heterogeneous set of autonomous data stores is combined and made available to data consumers as a single integrated data store via on-demand data integration.
 

What is meant by sharding?

Sharding is a method of partitioning a single dataset into many databases so that it may be stored on multiple machines.

Conclusion 

In this article, we have extensively discussed the difference between data virtualization and data federation.

We hope that this article has helped you enhance your knowledge regarding Data virtualization vs. Data federation and if you would like to learn more, check out our article on Hbase Columnar Database.

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