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The database development life cycle
The database development life cycle

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1.6 Implementation

Implementation involves the construction of a database according to the specification of a logical schema. This will include the specification of an appropriate storage schema, security enforcement, external schema, and so on. Implementation is heavily influenced by the choice of available DBMS, database tools and operating environment. There are additional tasks beyond simply creating a database schema and implementing the constraints – data must be entered into the tables, issues relating to the users and user processes need to be addressed and the management activities associated with wider aspects of corporate data management need to be supported. In keeping with the DBMS approach we want as many of these concerns as possible to be addressed within the DBMS. We look at some of these concerns briefly now.

In practice, implementation of the logical schema in a given DBMS requires a very detailed knowledge of the specific features and facilities that the DBMS has to offer. In an ideal world, and in keeping with good software engineering practice, the first stage of implementation would involve matching the design requirements with the best available implementing tools and then using those tools for the implementation. In database terms, this might involve choosing vendor products whose DBMS and SQL variants are most suited to the database we need to implement. However, we don't live in an ideal world and more often that not, hardware choice and decisions regarding the DBMS will have been made well in advance of consideration of the database design. Consequently, implementation can involve additional flexing of the design to overcome any software or hardware limitations.

Exercise 5

Summarise the reason why we want as much of the data management as possible to be addressed within the DBMS.


In a typical database system, different users and user processes share data – the alternative to putting the data management in the DBMS with the data is to duplicate the data management requirements in every application that uses the data. The more we can put in the DBMS, the less we have to implement in our user processes.