Data federation is a software process that allows multiple databases to function as one. It is a type of meta-database management system that transparently maps multiple autonomous database systems into a single federated database. The constituent databases are interconnected via a computer network and may be geographically decentralized. Data federation doesn’t consolidate information or eliminate other sources. Instead, it leaves the data in the location it already resides while using virtualization techniques to provide a unified view of the information. Data federation is a data management strategy that can help improve data quality as well as data accessibility.
Some key features of data federation include:
- Virtual database: A federated database, or virtual database, is a composite of all constituent databases in a federated database system.
- Uniform user interface: Through data abstraction, federated database systems can provide a uniform user interface, enabling users and clients to store and retrieve data from multiple noncontiguous databases with a single query—even if the constituent databases are heterogeneous.
- Federated queries: Data federation makes it simple to access your information by executing federated queries. These data access points are usually quite easy to use.
Data federation is different from data integration, which combines various data types and formats from an organization’s data sources into a data lake or data warehouse to provide a unified fact base for analytics. Data federation allows data to be accessed using standard interfaces such as ODBC and JDBC, vastly simplifying querying and analyzing information.
Data federation is an important data management strategy in today’s data-driven world, as it can help manage all of the information generated and collected every minute. It is an excellent tool for short-term use cases that don’t need to scale, enabling business users to forgo more resource-intensive, technical data integration.
