Comparar métodos

	Otimização de Consultas	Normalização de Banco de Dados	Estratégia de Indexação
Área	Sistemas de informação	Sistemas de informação	Sistemas de informação
Família	Process / pipeline	Process / pipeline	Process / pipeline
Ano de origem	1979	1970	1972
Autor original	IBM San Jose Research Laboratory	Edgar F. Codd	Rudolf Bayer and Edward M. McCreight
Tipo	Database optimization technique	Data organization methodology	Database optimization technique
Fonte seminal	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.
Outros nomes	—	—	index design, indexing
Relacionados	2	1	1
Resumo	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.