DBMS selection

Ebook "Relational database index design and the optimizers" includes content: Introduction, table and index organization, SQL processing, deriving the ideal index for a SELECT, proactive index design, factors affecting the index design process, reactive index design, indexing for table joins, star join considerations, indexes and reorganization; DBMS-Specific indexing restrictions, DBMS-Specific indexing options, optimizers are not perfect, additional estimation considerations, organizing the index design process.

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After completing this chapter, students will be able to: Relational operations unary , relational algebra operations from set theory, binary relational operations, additional relational operations , brief introduction to relational calculus.

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A crucial property of a relational DBMS is that it provides physical data independence. This allows physical structures such as indexes to change seamlessly without affecting the output of the query; but such changes do impact efficiency. Thus, together with the capabilities of the execution engine and the optimizer, the physical database design determines how efficiently a query is executed on a DBMS. The first generation of relational execution engines were relatively simple, targeted at OLTP, making index selection less of a problem.

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Data preparation includes the processes of cleansing, summarizing, and transforming detail and operational data into structures such as data warehouses and data marts that are suitable for BI reporting, data mining, scoring, and statistical processing. Many DBMSs provide some support for data preparation, such as filtering, aggregation, denormalization, and so on. However, SAS uniquely supports operations such as sampling, variable binning, imputation, and variable selection, which are typically not as robust in the DBMS functionality.

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