DBMS Concepts

DBMS Tutorial Components of DBMS. Applications of DBMS The difference between file system and DBMS. Types of DBMS DBMS Architecture DBMS Schema Three Schema Architecture. DBMS Languages.

DBMS ER Model

ER model: Entity Relationship Diagram (ERD) Components of ER Model. DBMS Generalization, Specialization and Aggregation.

DBMS Relational Model

Codd’s rule of DBMS Relational DBMS concepts Relational Integrity Constraints DBMS keys Convert ER model into Relational model Difference between DBMS and RDBMS Relational Algebra DBMS Joins

DBMS Normalization

Functional Dependency Inference Rules Multivalued Dependency Normalization in DBMS: 1NF, 2NF, 3NF, BCNF and 4NF

DBMS Transaction

What is Transaction? States of transaction ACID Properties in DBMS Concurrent execution and its problems DBMS schedule DBMS Serializability Conflict Serializability View Serializability Deadlock in DBMS Concurrency control Protocols

Difference

Difference between DFD and ERD

Misc

Advantages of DBMS Disadvantages of DBMS Data Models in DBMS Relational Algebra in DBMS Cardinality in DBMS Entity in DBMS Attributes in DBMS Data Independence in DBMS Primary Key in DBMS Foreign Key in DBMS Candidate Key in DBMS Super Key in DBMS Aggregation in DBMS Hashing in DBMS Generalization in DBMS Specialization in DBMS View in DBMS File Organization in DBMS What Is A Cloud Database What Is A Database Levels Of Locking In DBMS What is RDBMS Fragmentation in Distributed DBMS What is Advanced Database Management System Data Abstraction in DBMS Checkpoint In DBMS B Tree in DBMS BCNF in DBMS Advantages of Threaded Binary Tree in DBMS Advantages of Database Management System in DBMS Enforcing Integrity Constraints in DBMS B-Tree Insertion in DBMS B+ Tree in DBMS Advantages of B-Tree in DBMS Types of Data Abstraction in DBMS Levels of Abstraction in DBMS 3- Tier Architecture in DBMS Anomalies in Database Management System Atomicity in Database Management System Characteristics of DBMS DBMS Examples Difference between Relational and Non-Relational Databases Domain Constraints in DBMS Entity and Entity set in DBMS ER Diagram for Banking System in DBMS ER Diagram for Company Database in DBMS ER Diagram for School Management System in DBMS ER Diagram for Student Management System in DBMS ER Diagram for University Database in DBMS ER Diagram of Company Database in DBMS Er Diagram Symbols and Notations in DBMS How to draw ER-Diagram in DBMS Integrity Constraints in DBMS Red-Black Tree Deletion in DBMS Red-Black Tree Properties in DBMS Red-Black Tree Visualization in DBMS Redundancy in Database Management System Secondary Key in DBMS Structure of DBMS 2-Tier Architecture in DBMS Advantages and Disadvantages of Binary Search Tree Closure of Functional Dependency in DBMS Consistency in Database Management System Durability in Database Management System ER Diagram for Bank Management System in DBMS ER Diagram for College Management System in DBMS ER Diagram for Hotel Management System in DBMS ER Diagram for Online Shopping ER Diagram for Railway Reservation System ER Diagram for Student Management System in DBMS Isolation in DBMS Lossless Join and Dependency Preserving Decomposition in DBMS Non-Key Attributes in DBMS Data Security Requirements in DBMS DBMS functions and Components What is Homogeneous Database? DBMS Functions and Components Advantages and Disadvantages of Distributed Database Relational Database Schema in DBMS Relational Schema

Enforcing Integrity Constraints in DBMS

Introduction

Integrity constraints are rules that specify the conditions that must be met for the data in a database to be considered valid. These constraints help to ensure the accuracy and consistency of the data by limiting the values that can be entered for a particular attribute and specifying the relationships between entities in the database.

There are several types of integrity constraints that can be enforced in a DBMS:

  • Domain constraints: These constraints specify the values that can be assigned to an attribute in a database. For example, a domain constraint might specify that the values for an "age" attribute must be integers between 0 and 120.
  • Participation constraints: These constraints specify the relationship between entities in a database. For example, a participation constraint might specify that every employee must be assigned to a department.
  • Entity integrity constraints: These constraints specify rules for the primary key of an entity. For example, an entity integrity constraint might specify that the primary key cannot be null.
  • Referential integrity constraints: These constraints specify rules for foreign keys in a database. For example, a referential integrity constraint might specify that a foreign key value must match the value of the primary key in another table.
  • User-defined constraints: These constraints are defined by the database administrator and can be used to specify custom rules for the data in a database.

Ways to Enforce Integrity Constraints

There are several ways to enforce integrity constraints in a DBMS:

  • Declarative referential integrity: This method involves specifying the integrity constraints at the time of database design and allowing the DBMS to enforce them automatically.
  • Triggers: A trigger is a special type of stored procedure that is executed automatically by the DBMS when certain events occur (such as inserting, updating, or deleting data). Triggers can be used to enforce integrity constraints by checking for and rejecting invalid data.
  • Stored procedures: A stored procedure is a pre-defined set of SQL statements that can be executed as a single unit. Stored procedures can be used to enforce integrity constraints by performing checks on the data before it is inserted, updated, or deleted.
  • Application-level code: Integrity constraints can also be enforced at the application level by writing code to check for and reject invalid data before it is entered into the database.

It is important to carefully consider the appropriate method for enforcing integrity constraints in a DBMS in order to ensure the accuracy and consistency of the data.