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
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.