Definition
Schema evolution deals with the need to retain current data when database schema changes are performed. Formally, Schema Evolution is accommodated when a database system facilitates database schema modification without the loss of existing data, (q.v. the stronger concept of Schema Versioning) (Schema evolution and schema versioning has been conflated in the literature with the two terms occasionally being used interchangeably. Readers are thus also encouraged to read also the entry for Schema Versioning.).
Historical Background
Since schemata change and/or multiple schemata are often required, there is a need to ensure that extant data either stays consistent with the revised schema or is explicitly deleted as part of the change process. A database that supports schema evolution supports this transformation process.
The first schema evolutioning proposals discussed database conversion primarily in terms of a set of transformations from one schema to another [10]. These...
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Bancilhon F, Spyratos N. Update semantics of relational views. ACM Trans Database Syst. 1981;6(4):557–75.
Bretl R, Maier D, Otis A, Penney J, Schuchardt B, Stein J, Williams EH, Williams M. The GemStone data management system. In: Kim W, Lochovsky F, editors. Object-oriented concepts, databases and applications. New York: ACM; 1989. p. 283–308.
Hick JM, Hainaut JL. Database application evolution: a transformational approach. Data Knowl Eng. 2006;59(3):534–58.
Hull R. Relative information capacity of simple relational database schemata. Soc Ind Appl Math. 1986;15(3):856–86.
Kim W, Chou H.T. Versions of schema for object-oriented databases. In: Proceedings of the 24th International Conference on Very Large Data Bases; 1988. p. 148–59.
Melnik S, Rahm E, Bernstein PA. Rondo: a programming platform for generic model management. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 2003. p. 193–204.
Miller R, Ioannidis Y, Ramakrishnan R. The use of information capacity in schema integration and translation. In: Proceedings of the 19th International Conference on Very Large Data Bases; 1993. p. 120–33.
Ra YG, Rundensteiner EA. A transparent schema-evolution system based on object-oriented view technology. IEEE Trans Knowl Data Eng. 1997;9(4):600–24.
Roddick JF. SQL/SE – a query language extension for databases supporting schema evolution. ACM SIGMOD Rec. 1992;21(3):10–6.
Shneiderman B, Thomas G. An architecture for automatic relational database system conversion. ACM Trans Database Syst. 1982;7(2):235–57.
Sjøberg D. Quantifying schema evolution. Inf Softw Technol. 1993;35(1):35–44.
Tan L, Katayama T. Meta operations for type management in object-oriented databases - a lazy mechanism for schema evolution. In: Proceedings of the 1st International Conference on Deductive and Object-Oriented Databases; 1989. p. 241–58.
de Vries D, Roddick JF. The case for mesodata: an empirical investigation of an evolving database system. Inf Softw Technol. 2007;49(9–10):1061–72.
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Roddick, J.F. (2018). Schema Evolution. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_1532
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