Comparer des méthodes

	Optimisation des requêtes	Normalisation de base de données	Stratégie d'indexation
Domaine	Systèmes d'information	Systèmes d'information	Systèmes d'information
Famille	Process / pipeline	Process / pipeline	Process / pipeline
Année d'origine	1979	1970	1972
Auteur d'origine	IBM San Jose Research Laboratory	Edgar F. Codd	Rudolf Bayer and Edward M. McCreight
Type	Database optimization technique	Data organization methodology	Database optimization technique
Source fondatrice	Jarke, M., & Koch, J. (1984). Query optimization in database systems. ACM Computing Surveys, 16(2), 111-152.	Codd, E. F. (1970). A relational model of data for large shared data banks. Communications of the ACM, 13(6), 377-387.	Bayer, R., & McCreight, E. (1972). Organization and maintenance of large ordered indices. Acta Informatica, 1(3), 173-189.
Alias	—	—	index design, indexing
Apparentées	2	1	1
Résumé	Query optimization is a critical process in database management that transforms high-level SQL queries into efficient execution plans. Developed systematically by IBM researchers in the late 1970s, it aims to minimize execution time, disk I/O, and resource consumption by selecting the most effective access paths and join strategies.	Database normalization is a systematic process for organizing relational database schemas to eliminate redundancy and enforce data integrity. Introduced by Edgar Codd in 1970-1971 as part of the relational database model, it defines a series of normal forms (1NF through BCNF) that progressively eliminate different types of data anomalies.	Indexing strategy is the practice of systematically designing database indexes to accelerate query performance. Developed following Bayer and McCreight's foundational B-tree work in 1972, effective indexing requires analyzing query patterns, choosing appropriate index structures, and maintaining index health as data evolves.