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

Codds Rule of DBMS

Codd’s Rule of DBMS

Database having certain constraints and tables, need not to be a relational database system always. For perfect database management system, there are certain rules for the database, popularly known as Codd’s 13 (0 to 12) rules. These rules were proposed by Dr Edgar Frank Codd (EF Codd) in 1985 to define a perfect relational database system. For a relational database to be a perfect, it has to follow its rules. But, no RDBMS can follow or obey all its rules. Oracle database only obeys 8.5 rules out of 13.
A database management system that satisfies Codd’s rules is called a fully relational database management system.

The Codd’s 13 rules (0 to 12) for the relational databases are as follows:

Rule 0: Foundation Rule
This rule defines that for a system to qualify as an RDBMS, it must be able to manage the database entirely through the relational capabilities.

Rule 1: Information Rule
This rule defines that the data stored in the relational model is in the form of rows and columns of tables.

Rule 2: Guaranteed Access Rule
This rule defines that every data should be logically accessible through the combination of a table name, primary key, and name of the attribute or column.

Rule 3: Systematic Treatment of NULL values
In a relational database, NULL values represent the missed and inapplicable information in a systematic way. A NULL value is a special value, which is neither zero nor empty string. All the database systems support the NULL value concept.

Rule 4: Dynamic On-Line catalog based on the relational model
This rule defines that the structure of the database must support online relational catalog that is accessible to authorized users using its regular query language.

Rule 5: Comprehensive Data sub-language Rule
This rule states that the database system should be accessible by language support for data definition, data manipulation, and transaction management operation (begin, commit, rollback, etc.).

Rule 6: View Updating Rule
This rule states that all the views which are theoretically updated must be updated by the system (i.e. practical).

Rule 7: High-level Insertion, Updation and Deletion
This rule states that the relational database model must support insert, delete, and update operation on multiple rows.

Rule 8: Physical Data Independence
This rule states that the application program should remain unchanged whenever any change occur either in access methods or storage representation.

Rule 9: Logical Data Independence
This rule states that any changes in the conceptual or logical schema of a table should not enforce modification at application programs or External schema.

Rule 10: Integrity Independence

This rule states that a relational database system should support different constraints on data for data integrity. All the database system should support primary key constraint and foreign key constraint.

Rule 11: Distributed Independence
This rule implies that the user need not to be aware of whether a database is distributed over multiple locations or not. The user can access the data without any ambiguity from the different server.

Rule 12: Non-Subversion Rule
If the system provides a low-level interface, that interface cannot be used to subvert or not be able to bypass integrity rule to change data. This can be achieved by some encryption techniques.