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ADVANTAGES OF A DBMS
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Using a DBMS to manage data has many advantages: Data independence: Application programs should be as independent as possible from details of data representation and storage The DBMS can provide an abstract view of the data to insulate application code from such details E cient data access: A DBMS utilizes a variety of sophisticated techniques to store and retrieve data e ciently This feature is especially important if the data is stored on external storage devices Data integrity and security: If data is always accessed through the DBMS, the DBMS can enforce integrity constraints on the data For example, before inserting salary information for an employee, the DBMS can check that the department budget is not exceeded Also, the DBMS can enforce access controls that govern what data is visible to di erent classes of users Data administration: When several users share the data, centralizing the administration of data can o er signi cant improvements Experienced professionals who understand the nature of the data being managed, and how di erent groups of users use it, can be responsible for organizing the data representation to minimize redundancy and for ne-tuning the storage of the data to make retrieval e cient
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Introduction to Database Systems
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Concurrent access and crash recovery: A DBMS schedules concurrent accesses to the data in such a manner that users can think of the data as being accessed by only one user at a time Further, the DBMS protects users from the e ects of system failures Reduced application development time: Clearly, the DBMS supports many important functions that are common to many applications accessing data stored in the DBMS This, in conjunction with the high-level interface to the data, facilitates quick development of applications Such applications are also likely to be more robust than applications developed from scratch because many important tasks are handled by the DBMS instead of being implemented by the application Given all these advantages, is there ever a reason not to use a DBMS A DBMS is a complex piece of software, optimized for certain kinds of workloads (eg, answering complex queries or handling many concurrent requests), and its performance may not be adequate for certain specialized applications Examples include applications with tight real-time constraints or applications with just a few well-de ned critical operations for which e cient custom code must be written Another reason for not using a DBMS is that an application may need to manipulate the data in ways not supported by the query language In such a situation, the abstract view of the data presented by the DBMS does not match the application s needs, and actually gets in the way As an example, relational databases do not support exible analysis of text data (although vendors are now extending their products in this direction) If specialized performance or data manipulation requirements are central to an application, the application may choose not to use a DBMS, especially if the added bene ts of a DBMS (eg, exible querying, security, concurrent access, and crash recovery) are not required In most situations calling for large-scale data management, however, DBMSs have become an indispensable tool
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DESCRIBING AND STORING DATA IN A DBMS
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The user of a DBMS is ultimately concerned with some real-world enterprise, and the data to be stored describes various aspects of this enterprise For example, there are students, faculty, and courses in a university, and the data in a university database describes these entities and their relationships A data model is a collection of high-level data description constructs that hide many low-level storage details A DBMS allows a user to de ne the data to be stored in terms of a data model Most database management systems today are based on the relational data model, which we will focus on in this book While the data model of the DBMS hides many details, it is nonetheless closer to how the DBMS stores data than to how a user thinks about the underlying enterprise A semantic data model is a more abstract, high-level data model that makes it easier
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