Data Virtualization Tools

Data Virtualization Tools Overview

What are Data Virtualization Tools?

Data virtualization provides access to data while hiding technical aspects like location, structure, or access language. This allows applications to access data without having to know where it resides. This can be used in (for instance) data federation, where data in separate data stores are made to look like a single data store to the consuming application.

Data virtualization tools are confused with Enterprise Application Integration (EAI) as both concern data integration. But EAI supports passing data between enterprise applications. Data virtualization allows querying across multiple databases and data management tools as though they were one data store.

Data virtualization is also distinct from Extract, Transform, and Load (ETL) technologies which normalize and stream data to a data warehouse. Unlike ETL, data virtualization tools provide real-time answers to queries while the data remains in place without replication. Data virtualization tools are faster and less resource intensive than ETL.

Data Virtualization Tools Features & Capabilities

Data virtualization tools generally provide these features:

• Treat multiple data sources as a single source

• Combine, transform data to produce virtual data model

• Graphical or codeless data modeling, data design tools

• Advanced transformation (e.g. for non-relational data)

• Virtualize real-time access to data without moving it

• Advanced query engine

• Centralize metadata control

• User-friendly view of enterprise data

• On-demand data publication

• Business directory and controlled, easy data search

• Virtual data layer provides data firewall, secure access control

Pricing Information

Data virtualization provides a relatively inexpensive means of acting upon combined data from disparate sources. Many tools are available on a trial basis, after which they are available on a monthly or annual subscription. Licensing cost scales with the number of data sources drawn from, as well as the number of queries to be run.