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WHAT IS A REALATIONAL DATABASE MANAGEMENT SYSTEM (RDBMS)

VIDYABHARTI TRUST COLLEGE OF BBA & BCA. UMRAKH

SUBJECT: RDBMS

COURSE: BCA SEM: III

WHAT IS A REALATIONAL DATABASE MANAGEMENT SYSTEM (RDBMS)

A Relational Database Management system (RDBMS) is a database management system (DBMS) that is based on the relational model as introduced by Dr. Edgar F. Codd. Strictly speaking it should also satisfy codd’s 12 rules, but in practice there is no DBMS that satisfies all these rules. In fact, most successful DBMS that are considered to be relational violate the relational model in several important ways, including the structured Query language (SQL). However, most database practitioners and researchers use the term in a loose way such that most databases that support SQL are included.

Relational Database Management system (RDBMS) stores data in the form of related tabled. RDBMS are powerful because they require few assumptions about how data is related or how it will be extracted from the database. As a result, the same database can be viewed in many different ways.

An important feature of relational systems is that a single database can be spread across several tables. This differs from flat file database, in which each database is self- contained in a single table.

The first released RDBMS that was a relatively faithful implementation of the relational model was the Multics Relational Data store first sold in 1978. Others have been Berkeley Ingres, QUEL and IBM BS12.

Today, popular commercial RDBMS for large databases include Oracle Microsoft SQL server, sybase SQL server, and IBM’s DB2. The most commonly used free RDBMS are MySQL, postgreSQL.

Dr. E. F. Codd’s Rules for RDBMS

Dr. E. F. Codd is an IBM researcher who first developed the relational data model in 1970. In 1985, Dr. Codd published a list of 12 rules that define ideal relational database and has provided a guideline for the design of all relational database systems.

Dr. Codd has used the term guideline because till date no commercial relational database system fully conforms to all 12 rules. For a few years, scorecards were kept that rated each commercial product’s conformity to Codd’s rules. Today, the rules are not talked about as much but remain a goal for relational database design.

· Rule 1: The Information Rule:

· All data should be presented in table form.

· Means CLIENT_MASTER table represent following:

TABLE: CLIENT_MASTER

COMMAND:

CREATE TABLE CLIENT_MASTER

(

CLIENTNO VARCHAR2(6) PRIMARY KEY,

NAME VARCHAR2(20) NOT NULL,

ADDRESS1 VARCHAR2(30),

ADDRESS2 VARCHAR2(30),

CITY VARCHAR2(15),

PINCODE NUMBER(8),

STATE VARCHAR2(15),

BALDUE NUMBER(10,2)

);

STRUCTURE:

Name Null? Type

---------------------------- -------- ----

CLIENTNO NOT NULL VARCHAR2(6)

NAME NOT NULL VARCHAR2(20)

ADDRESS1 VARCHAR2(30)

ADDRESS2 VARCHAR2(30)

CITY VARCHAR2(15)

PINCODE NUMBER(8)

STATE VARCHAR2(15)

BALDUE NUMBER(10,2)

· Rule 2: Guaranteed Access Rules:

· All data should be accessible without ambiguity.

· This can be accomplished through a combination of the table name, Primary Key, and column name.

· EXAMPLE:

Emp_info

Emp_Salary_info

EmpId

Name

EmpId

Salary

91

John

91

20000

92

Thomas

92

40000

OR

· Each and every data is guaranteed to be logically accessible by resorting to a combination of table name, primary key value and column name.

· Rule 3: Systematic Treatment of Null Values:

· A field should be allowed to remain empty.

· This involves the support of a null value, which is distinct from an empty string or number with a value of zero.

· Of course, this can’t apply to primary key. In addition, most database implementations support the concept of a not- null field constraint that prevents null values in a specific table column.

· EXAMPLE:

Emp Id

Name

Phone No

Mobile No

09BCA01

John

2326864

9725142752

09BCA02

Thomas

2555631

-

· NULL Values are supported in the fully relational DBMS for representing missing information in a systematic way independent of data type.

· NULL values are distinct from empty character string or a string of blank character and distinct from 0 or any other number.

· Rule 4: Dynamic On-Line Catalog based on the Relational Model:

· A relational database must provide access to its structure through the same tools that are used to access the data.

· EXAMPLE:

This is usually accomplished by storing the structure definition within special system tables.

· Rule 5: Comprehensive Data Sublanguage Rule:

· The Relational database must support at least one clearly defined language that includes functionality for data definition, data manipulation, data integrity and database transaction control.

1. Data Definition

2. View Definition

3. Data Manipulation

4. Integrate Constraints

5. Authorization

6. Transaction Control

· All commercial relational database use forms of standard SQL (i.e. Structure Query Language) as their supported comprehensive language.

· Rule 6: View Updating Rule:

· Data can be presented in different logical combination called views.

· Each view should support the same full range of data manipulation that has direct access to a table available.

· In practice, providing update and delete access to logical view is difficult and not fully supported by any current database.

· EXAMPLE:

All views those are theoretically updatable by the system.

This rule is not really implemented yet any available.

· Rule 7: High –Level Insert, Update, and Delete:

· Data can be retrieved from a relation database in sets constructed of data from multiple rows and/or multiple tables.

· This rule states that insert, update, and delete operations should be supported for any retrievable set rather than just for a single row in a single table.

· EXAMPLE:

Suppose if we need to change ID then it will reflect everywhere automatic.

· Rule 8: Physical Data independence:

· The user is isolated from the physical method of storing and retrieving information from the database.

· Changes can be made to the underlying architecture (hardware, disk storage methods) without affecting how the user accesses it.

· EXAMPLE:

The user is isolated (Separated) from the physical method of storing and retrieving information from the database in which affecting directly in database.

· Rule 9: Logical Data Independence:

· How data is viewed should not be changed when the logical structure (table’s structure) of the database changes.

· This rule is particularly difficult to satisfy.

· Most databases rely on strong ties between the data viewed and the actual structure of the underlying tables.

· EXAMPLE:

In this rule we want to retrieve any ID, when we retrieve Data without ID that time we can not satisfy this rule.

· Rule 10: Integrity Independence:

· The database language (like SQL) should support constraints on user input that maintain database integrity.

· This rule is not fully implemented by most major vendors.

· At a minimum, all databases do preserve two constraints through SQL.

· No component of a primary key can have a null value.

· If a foreign key is defined in one table, any value in it must exist as a primary key in another table.

· All databases do preserved to constrain through SQL.

1. Primary Key can not have NULL.

2. Foreign Key is define in one table any value in it must exists as a primary key in another table.

3. Integrity constraints specific to a particular relation database must be definable in the relational data sub-language & storable in a catalog not in the application program.

· Rule 11: Distribution independence:

· A user should be totally unaware of whether or not the database is distributed (whether parts of database exist in multiple locations) make this rule difficult to implement.

· A variety of reasons make this rule difficult to implement.

· EXAMPLE:

This rule difficult to implement due to variety of reasons.

· Rule 12: Non subversion Rule:

· There should be no way to modify the database structure other than through the multiple row database language (like SQL).

· Most databases today support administrative tools that a