Last Updated on April 17, 2023 by Prepbytes
Database Management System (DBMS) is a software system that manages data stored in databases. It provides a platform for users to create, retrieve, update, and delete data. One of the essential features of DBMS is the ability to handle different levels of abstraction. The concept of levels of abstraction in DBMS is important because it allows users to work with databases without worrying about the underlying implementation details. In this article, we will discuss the different levels of abstraction in DBMS.
Levels of Abstraction in DBMS
The three levels of abstraction in DBMS are:
- External Level / View Level
- Conceptual Level/ Logical Level
- Internal Level / Physical Level
The below image provides a clear view of the different levels of abstraction in DBMS.
Each level has its own purpose and functions, and they are connected to each other through mappings. Let us learn about each levels of abstraction in DBMS in detail.
Physical Level (External Level)
The external level, also known as the View level, is the level of abstraction that is closest to the end users. It defines how the data is viewed by the users or applications that access the database. It provides a high-level view of the database that is tailored to the specific needs of each user or application.
The external level includes the schema, which is a description of the data that is relevant to a specific user or application. The schema defines the tables, attributes, and relationships that are relevant to the user or application. Users or applications interact with the database through the schema, which provides a simplified view of the database that is easy to understand and use.
The external level is designed to provide a level of abstraction that shields the users or applications from the complexities of the underlying database. It allows users to work with the data in a way that is meaningful to them without worrying about the details of how the data is stored or organized.
Conceptual Level (Logical Level)
The conceptual level, also known as the logical level, is the level of abstraction that defines the overall structure of the database. It defines the relationships between the data elements, the constraints on the data, and the operations that can be performed on the data.
The conceptual level includes the data model, which is a representation of the data that is independent of any specific database management system. The data model defines the tables, attributes, and relationships that make up the database and the constraints that govern them.
The conceptual level is designed to provide a high-level view of the database that is independent of any specific implementation. It allows users to define the structure of the database in a way that is meaningful to them without worrying about the details of how the data is stored or accessed.
Physical Level (Internal Level)
The internal level, also known as the physical level, is the level of abstraction that defines how the data is physically stored and organized in the database. It includes the details of how the data is stored on disk, the access methods used to retrieve the data, and the algorithms used to perform operations on the data.
The internal level includes the physical schema, which is a description of how the data is physically stored in the database. The physical schema defines the data structures used to store the data, the access methods used to retrieve the data, and the algorithms used to perform operations on the data.
The internal level is designed to provide a low-level view of the database that is optimized for performance and efficiency. It allows database management systems to store and access data in the most efficient way possible, without worrying about the needs of the users or applications.
For a deeper understanding of the topic, you can refer to the blog – DBMS Architecture.
Benefits of Levels of Abstraction in DBMS
The levels of abstraction in DBMS provide several benefits to users and applications, including:
- The levels of abstraction in DBMS provide a separation between the way data is viewed by users or applications and how it is stored and accessed by the database management system. This allows changes to be made to the physical storage and access methods without affecting the external or conceptual levels.
- The levels of abstraction in DBMS make it easier for database administrators to manage the database. They can make changes to the physical storage and access methods without affecting the users or applications that interact with the database.
- The levels of abstraction in DBMS allow the database management system to optimize the physical storage and access methods for performance without affecting the way data is viewed by users or applications.
- The levels of abstraction in DBMS allow users or applications to view the data in a way that is meaningful to them without worrying about the underlying implementation details. This makes it easier to adapt to changing business requirements and user needs.
Conclusion
The levels of abstraction in DBMS provide a powerful tool for managing data in complex systems. They allow users and applications to work with the database in a way that is meaningful to them without worrying about the underlying implementation details. The levels of abstraction in DBMS provide data independence, simplified database management, improved performance, and flexibility. By understanding the different levels of abstraction and how they are connected through mappings, users, and applications can interact with the database in a way that is efficient, effective, and meaningful.
Frequently Asked Questions (FAQs)
Here are some Frequently Asked related to “Levels of Abstraction in DBMS”.
Ques 1. What is data independence in DBMS?
Ans. Data independence in DBMS refers to the ability to make changes to the physical storage and access methods without affecting the external or conceptual levels.
Ques 2. What is simplified database management in DBMS?
Ans. Simplified database management in DBMS refers to the ability for database administrators to make changes to the physical storage and access methods without affecting the users or applications that interact with the database.
Ques 3. What is a schema in DBMS?
Ans. A schema in DBMS is a description of the data that is relevant to a specific user or application. The schema defines the tables, attributes, and relationships that are relevant to the user or application.
Ques 4. What is a data model in DBMS?
Ans. A data model in DBMS is a representation of the data that is independent of any specific database management system. The data model defines the tables, attributes, and relationships that make up the database and the constraints that govern them.
Ques 5. What is mapping in DBMS?
Ans. Mapping in DBMS refers to the links between the different levels of abstraction in DBMS that allow the users or applications to interact with the database at the appropriate level of abstraction.