Federated database system

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A federated database system is a type of meta-database management system (DBMS) which transparently integrates multiple autonomous database systems into a single federated database. The constituent databases are interconnected via a computer network, and may be geographically decentralized. Since the constituent database systems remain autonomous, a federated database system is a contrastable alternative to the (sometimes daunting) task of merging together several disparate databases. A federated database (or virtual database) is the fully-integrated, logical composite of all constituent databases in a federated database system.

Through data abstraction, federated database systems can provide a uniform front-end user interface, enabling users and clients to store and retrieve data in multiple noncontiguous databases with a single query--even if the constituent databases are heterogeneous. To this end, a federated database system must be able to deconstruct the query into subqueries for submission to the relevant constituent DBMS's, after which the system must composite the result sets of the subqueries.

Because various database management systems employ different query languages, federated database systems can apply wrappers to the subqueries to translate them into the appropriate query languages.

[edit] Schema matching, schema mapping

Dealing with incompatible data types or query syntax is not the only obstacle to a concrete implementation of a FDBS. In systems that are not planned top-down, a generic problem lies in matching semantically equivalent, but differently named parts from different schemas (=data models) (tables, attributes). A pairwise mapping between n attributes would result in $n (n-1) \over 2$ mapping rules (given equivalence mappings) - a number that quickly gets too large for practical purposes. A common way out is to provide a global schema that comprises the relevant parts of all member schemas and provide mappings in the form of database views. Two principal solutions can be realized, depending on the direction of the mapping:

Global as View (GaV): the global schema is defined in terms of the underlying schemas
Local as View (LaV): the local schemas are defined in terms of the global schema

Both are explained in more detail in the article Data integration.