Relational Database , Relational Database Management System , RDBMS

Relational Database

Relational Database Management System

RDBMS | Relational Model | Data Modelling | Normalization

The Relational Database is a database that is designed and developed based on the relational database model . 

The Relational Database Model was  proposed and  developed by E.F. Codd  who was an English computer scientist  while he was working with  IBM .

The Relational Database  Management System ( RDBMS ) is a database management system ( DBMS ) that allows the creation , management and administration of Relational Databases.

Relational Database , Data , Database , RDBMS

What Is Relational Database ?

The Relational Databases are  the most commonly used databases in the industry today. Some  of the  most popular DBMS being used  are  based  on the relational model  . 

The most popular and widely used RDBMS  includes  MySQL , Oracle   MS SQL server and there are many more.

In this tutorial , you will learn what are relational databases , design principles , relational database terminology , database keys , database normalization and other important topics related to the relational databases.

What Is Data ?

The data is the central core of any database software application. The database applications are designed and developed to process large volumes data . let us first start with getting the clarity and understand the meaning of term data.

The data  is  the most  important  element  of any  database system. It is important to understand  the meaning of term data and what it means  to different database users .

The database users include  end users , database  designers , database application developers , system analysts and database administrators.

The term data  usually refers to raw data that has not been processed and therefore cannot be directly used for some meaningful work such as analyzing trends and decision making  within an organization.

What Is Data , Data Processing , RDBMS , Relational Database

The data is scientifically collected and recorded as   facts , observations  , factual information , set of values  and  figures about any real world objects. 

The data must be stored and digitally processed with the help of a computer system and software application to operate on the data.

For example if we are designing a database system to store the employee information,  then all the employee related data such as employee  Name , address , designation , DOB , Salary  will be stored in a database as employee data.

What Is Database ?

The database  is the well organized collection of  interrelated data  that can be easily  accessed , retrieved  and stored for any future use .  

The  databases  are  created  , administered  and  managed  by using  any  DBMS  software such as MySQL which is a type of  RDBMS.

The  database  is  a  key  component of  most of the software applications  which are designed  to  store the  information about  some real world business entities such as  employee database , customer database ,  student database , inventory management system  and so on .

What Is Database , RDBMS
What Is Database , RDBMS , Database

The data within a database can be easily accessed and processed , since the data in a database is  logically organized and inter-related. A  Database is a computer based  record keeping system which is used to record , maintain and retrieve data .

The database is a vital component any database management system ( DBMS ) that actually stores the data . The database allows various operations for efficiently storing , retrieving  and  managing  the  data within a database .  

What Is Relational Database ?

The  relational databases implement the relational model invented and proposed by E F Codd . The relational databases are designed as per the set of rules and principles defined by E F Codd.

In relational database management system the logical structure of the database consist of number of inter-related tables . 

A Table represents a relation or database entity. A table is a collection of records and each table row represents a record . Each table in a relational database consist of number of rows and column .

RDBMS Relational DB Structure
RDBMS Relational DB Table Example

What Is RDBMS ?

Relational Database Management System

The RDBMS stands for Relational Database Management System. The RDBMS is a software application designed to create , manage and administer the relational databases . 

The RDBMS internally might consist of number of sub-programs  and each of these program performs a specific operation of the RDBMS.

The RDBMS is a database management system that is based on the relational model proposed and  developed by E.F. Codd  who was an English computer scientist. He invented and proposed the theory of Relational Databases while he was working with IBM .

The user interacts with the database through application software ( Front End ) . The application software in turn use SQL which is database query language . 

The DBMS in turn interacts with the database and perform various database operations . The RDBMS provides a layer of abstraction between database and application software.

What Is RDBMS

The Relational Database Management System ( RDBMS ) is the most commonly used DBMS  in the industry today. Some  of the  most popular and widely used RDBMS  include MySQL , Oracle  and   MS SQL Sever.

The RDBMS supports only relational databases . The relational databases are based on the relational model . The relational databases must comply the set of rules defined by E F Codd  in order to qualify as relational database.

Relational Database Management System

Most Widely Used RDBMS

The database technology has evolved over a period of last few decades and seen the advent of different types of database management systems such as NoSQL and Object oriented databases .

However, despite these developments , the RDBMS technology has retained its popularity. 

The RDBMS market has seen a steady growth despite the advent of new players. The RDBMS market is dominated by some of the largest players such as  Oracle , IBM and Microsoft . 

The most popular and widely used RDBMS include :

Relational Database Terminology

In order to understand the relational database structure , It is important to first understand the relational database terminology. This terminology includes the frequently used technical terms . Some of the frequently used terms include :

Entity

What Is Entity In Database Design ?

A database entity is any object or business concept that needs to be represented within a database system . 

An entity can also be an object or concept that we want to model and store information about. A database entity could be any recognizable concepts which may be either concrete ( Tangible ) or abstract ( Intangible ) .

For example let us consider a database for a college . The student , teacher , principal , department , major are all examples of valid objects or database entities . The database stores  information about various entities within a database .

Attributes

What Are The Attributes Of An Entity ?

Each database entity has many attributes which highlight a specific feature of the database entity . Each table column represents one attribute of database entity.

For example , let us consider a students database. The student is a valid database entity and the first name , last name , DOB , SSN are some the attributes which are represented by respective column in the student table.

Database Entity And Attribute
Entity Relationship Diagram

Relationship

What Is Relationship In Relational Database ?

In relational database the  logical structure of the database consist of number of interrelated tables . Each  table represents  an entity . The relationship is an association between the two database entities .

In relational  database , an entity  is  represented  by a table  which  is  also commonly referred  as  a relation . So  each  entity  is  a  type  of  relation . Since  the  relation  is  a mathematical  construct ,  it  can easily  be  represented  as  two  dimensional  table .

The relationship between the two tables (  Entities ) is defined by using the database keys that is primary key and foreign key .

Relational Database

Database Keys

What Are Database Keys ?

The relational database consist of number of inter related tables . The relationship is an association between the tables , which depends upon the functional dependencies.

In relational  database , an entity  is  represented  by a table  which  is  also commonly referred  as  a relation . So  each  entity  is  a  type  of  relation . Since  the  relation  is  a mathematical  construct ,  it  can easily  be  represented  as  two  dimensional  table .

The DBMS can access a specific data value stored into a data field ( intersection of row and column ) with reference to column name  and  a  unique row for each record . 

This unique attribute for each record in a table is defined as database key . The database key  has  a  unique value  for  each   table row  (Record /  Tuple). 

Types Of Database Keys

Relational Database Keys , Database Keys , Primary Key , Foreign Key

Relational Database

Types Of Database Keys

The  database designers define the relationship between the  tables , with the help of different types of database keys. 

In relational  database , the database keys can be  fundamentally grouped  in to two categories ( Unique  Keys   And    Non Unique  Keys )  based  on the uniqueness  of the  column (  Attribute  ) values.

The  unique  keys  can be further  subdivided as Super Keys , candidate key  , Composite key , Primary  Key  and  Surrogate  key    And  Foreign key is  a  Non unique key.

Database Keys Types
Relational Database Model

Relational Database

What Is SQL ?

Structured Query Language

The SQL stands for Structured Query Language . In simple terms ,it is a database query language ( type of computer language ) used by the software applications to communicate with the database management system ( DBMS ) . 

The DBMS in tern communicates with the database . The DBMS also manages the actual database that stores the data.

The RDBMS – Relational Database Management System are  extensively being used for providing  web server based  database functionality  to  some  of the largest  and  popular  web applications .

The RDBMS internally makes use of SQL – Structured Query Language  which is a database query language used  for  performing  various  database  operations  on the  relational  databases.

Structured Query Language
What Is SQL , Structured Query Language

The Structured Query Language ( SQL ) is a database query language used for storing and managing data the using any  RDBMS. SQL was the first commercial language introduced for E.F Codd’s Relational Database Model. The SQL is supported by almost all RDBMS currently operational.

Today, almost all RDBMS ( MySql, Oracle, MS SQL Server , Sybase, MS Access ) use SQL as the standard database query language. SQL is used to perform all types  of   database  operations  in  RDBMS.   

Relational Database

Data Modelling

What Is Data Modeling ?

Similar to an architect , the database designers also create a data model during database design process  to visualize and communicate the design features of the database being designed  . These  data models are later on used  as  blue prints for building the database.

In the context of database design , a data model is simply a diagrammatic representation of the database’s internal structural details  . In  other words , a  data model is simply a diagram that displays  a  set of tables ( database entities )  and the relationship between these tables .

The  data model makes it very easy  to  understand  how  different database entities are being  represented by tables and Relationships ( functional dependencies ) that exists between these tables .

Types Of Data Models

Data Models , How To Design Database

Data Models In DBMS

Data Models In Database Development

Data Modelling

Conceptual , Logical And Physical Data Model

A   data model  is  constructed  as conceptual data model, logical data model  and  physical data Model . Each data model   highlights  different  database design  features  and  presents  different  abstraction view.

The conceptual, logical and physical  data  models are three different ways of modelling data during database design process .

Conceptual Data Model

During  the database  design process  the  database  designers  create  a conceptual data  model  to capture the  end user  data  requirements  that user needs  to  perform  specific role  within  an  organization.

The  Entity  Relationship  Diagram ( ERD )  is  a graphical conceptual representation of the database used by the database designers   to  define  the  database  view  at the  end  user  level.

Conceptual Data Model
Conceptual Data Model Features

In other words, the conceptual data model is a graphical description of the business . The conceptual data model helps to identify the key business entities and systems that needs to be represented in the database.

The conceptual data model is a highly abstract and provides a high-level view of the key business and system entities and the association between them in terms of existing relationships.

The conceptual data model is DBMS independent and can be implemented on any DBMS .

Logical Data Model

The logical data model is the second stage of the database design process   and  can be implemented on any DBMS .

The logical data model is created from   conceptual data model . The conceptual data model is  further expanded by database designers by adding more details  which brings further clarity  and detailing about the database structural  elements .  

A logical data model describes the relationships  between the various tables ( entities )  by identifying the primary key and foreign keys  for  each table  and the relationships are defined with the help of  connecting  arrow  depending upon the functional  dependencies .

Logical Data Model , Database Design Process
Logical Data Model Features

 A  logical  data model diagram can be drawn with  the help of a special software  such as Erwin , ER/One and many more .

The logical data model is DBMS independent and can be implemented on any DBMS .

Physical Data Model

The physical data model is the third stage of the database design process   and  can be implemented  only on  specific  DBMS .

The physical data model is created from   logical data model . The logical data model is  further expanded by database designers by adding more details  which are required to create a database using specific  DBMS such as  data type and size for each data field.

A  physical data model refers  the  database entities  as tables  and  entity  attributes  as  table columns .

Physical Data Model

In  physical data model , the  column names are  not user friendly names but column names must be database compatible names  in which the  database will be created such as  MySQL Or  Oracle  Or  any other database .

In physical data model  the  data type  and size should also be fully compatible with the DBMS used to create the database .

The physical data model constrains database developers to define the data type and size . And therefore , the physical data model is DBMS dependent and can be implemented only on specific DBMS that supports the same data type.

Introduction To Relational Database Model

The  Relational Database Model  is one of the most important database model and the relational databases are extensively being  used in the industry . 

The  relational database model offers major advantages  as compared  to traditional computer based record keeping system .

In order to understand the advantages offered by the relational databases , the database student needs to be aware of the limitations of traditional single table databases .

Flat File Database

Limitations Of Flat File Databases

The traditional computer based record keeping system used to store the data is single flat file or in a single table . The single table database has some major limitations and it is difficult to establish relationship between between various data elements .

Further , In a single table database  it is difficult to control the repetition of data in a multiple rows and columns . These duplication of same data at  multiple places leads to problem of data redundancy. 

The data redundancy is the root cause of  many database problems  ( Database Anomalies ) and inconsistent state of the database.

Data Redundancy

What Is Data Redundancy ?

The presence same data in multiple records is referred as redundant data . This repetition of data at multiple places within a table is the root cause of many potential problems  . 

The redundant data can be either present at multiple fields of the same table or it can be present in number of tables.

The data redundancy problem must be resolved to avoid various database anomalies . The database anomalies leads to inconsistent state of the database when database contains two different values for same data field.

These problems due to the presence of redundant data in a table are referred as database anomalies. 

In single large table database , it is difficult to avoid redundant data . And therefore , in relational database, the larger tables are decomposed to smaller tables in order to normalize the database.

Example Of Data Redundancy

Data Redundancy

Let  us consider one example to illustrate  the existence of  redundant data in a table . 

As we see in this  table ,  the  table columns  Department Code , Department Name  and  Department  Head  are  being repeated as  duplicate  data fields  for  each  employee record which is a redundant data.

This  duplication of data in multiple records is referred  as  redundant data . The redundant data  is the root cause of many database anomalies. The data redundancy must  to be treated and  reduced to minimum.

Database Anomalies

What Are Database Anomalies ?

The  DBMS’s are  mainly used  to efficiently organize the data for its optimum utilization . 

In RDBMS ,  the data is logically organized as group of inter related tables . The database developers split the  larger tables into smaller but more meaningful tables to avoid the duplication of  data  in tables .

The presence of redundant data in a table can cause many potential problems commonly referred as database anomalies in the database world . 

The database anomalies caused due to redundant data adversely affect the database performance  and consequently  the applications which makes use of the database .

Database Anomalies In Relational Database , Database Normalization
Database Anomalies In Relational Database , Database Normalization

And therefore , during the database development process , the database is designed  by applying a set of rules ( Database Normalization Rules ) and by splitting  the larger tables into smaller tables  to avoid the data redundancy.

Relational Database

Types Of Database Anomalies

The  presence of duplication of data in a table can cause different types of database anomalies . The three database anomalies needs to be treated in order to normalize the database :

Insertion Database Anomaly

An  insert anomaly  is  said  to  be  present  in a table when certain attributes  cannot be inserted  into the database table  without the presence of  other  attribute . An  insertion anomaly is the inability to add data to  the  database  due to absence of  other data .

An insertion anomaly  makes  it  mandatory  to  first insert  some  other  data fields  in order  to  insert the required  data . An  insertion anomaly is caused  due to  the presence  of  redundant data  in  a un-normalized  table .   

Update Database Anomaly

An  update anomaly  is  said  to  be  present  in a table when the database operation fails to update all the records resulting inconsistent state of the database.

The update  ( Also referred as Modify Anomaly ) is caused  due to the presence of  redundant data in a table containing duplicate fields in multiple records . 

An  update anomaly is the inability to update all records within a database  table during update operation.

An  update anomaly is caused  due to  presence  of  redundant data  in a  un normalized  table and can be resolved by normalizing the tables.   

Deletion Database Anomaly

A  delete anomaly  is  said  to  be  present  in a table when the one  database delete operation on one attribute also  deletes  another attribute .

A deletion anomaly is the unintended loss of data during the one database delete operation on one set of data  that  causes  deletion of other data .

An  delete anomaly is caused  due to  the presence  of  redundant data  in a  un normalized  table and can be resolved by normalizing the tables.

Relational Database Design

The Relational database is logically structured as group of inter-related tables. The each table in a database represents a database entity . 

The relation is established between the tables  by defining a primary key for each table which has a unique value for each row ( record ) in a table .

A relationship is created when the primary key of one table is included as foreign key in another table as non-prime attribute . 

Each table can have only one primary key and many foreign keys as non prime attribute.

RDBMS Table Structure

Each table represents an entity . Each table consist of number of rows and columns . Each table row represents a unique record ( an instance ) which is uniquely identified by its corresponding primary key .

Each table represents an entity and each database entity can have many attributes . These attributes are represented by table columns for a relational table . Each attribute of the entity represents one table column.

Each  intersection of  table row and column represents a data field that can be uniquely identified with reference to primary key ( row ) and attribute name ( Column ) . And therefore , each data field ( Table Cell ) has unique identity .

E F Codd's 12 Rules For Relational Databases

The  Relational Databases are  well known for its reliability  , simplicity  , robustness and  security features  . E F Codd inventor of relational database model defined rules that relational database must comply.

The  Codd’s twelve rules are a set of  rules was  proposed by EF. Codd, , who introduced the  relational database model .  A DBMS must conform to these rules in order to qualify as a relational database .

The databases designed using  RDBMS  are based on relational model and  referred as relational databases . These twelve rules include :

Relational Database

Database Normalization

The  database normalization is an important step in the design process  of relational databases . To normalize the database  the larger tables are  split into the smaller tables to minimize the problems caused  due to duplication of data in tables. The main objective of the normalization process is to eleminate the database anomalies.

During the database design stage , the database designers main task is to reorganize the tables in such a manner that , the data redundancy minimized or completely eliminated .

Database Normalization

The  redundant data in table is the main cause of  various database anomalies and such problems must be resolved  in the database design stage . 

The process of reorganizing the data in a tables by splitting larger tables in to smaller meaningful tables with well defined relationships is referred as database normalization.

The main objective of the database normalization process is to minimize the problem of data redundancy in larger tables that causes  database anomalies. 

During the database normalization , the larger tables are decomposed to smaller meaningful tables by applying the  database normalization rules .

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What Is Database Normalization ?

E F Codd's

Database Normalization Rules

 Edgar F. Codd, was the inventor of the relational model . He also introduced the concept of database normalization which was based on his relational  model . 

E F Codd  proposed  three forms ( three stage process )  for  database normalization  what we today know as the  First Normal Form  ( 1NF ) in 1970. 

He subsequently also  went  on to define the Second Normal Form ( 2NF ) and  Third Normal Form (  3NF ) in 1971  for  database normalization .

Database Normalization And E F Codd Relational Model

Database Normalization Forms

E F Codd  was the  inventor of relational model and  proposed  three types  of  normal forms   ( 1NF , 2NF and 3NF )  for  the  normalization  of  tables  within  a  relational database .

He  also  defined the normalization  rules  that each table in a relational database  must satisfy  and  also the corrections  to be applied to the table  so that  the table  qualify   to  the  different criterion defined  for  normalization ( 1NF , 2NF and 3NF )  .

The  table which is  in  2NF  is also  considered to be  in  1NF  and  the table which is in  3NF  is  also considered to be   in  1NF   and  2NF .

Database Normalization Rules

Database Normalization

First Normal Form ( 1NF )

The  relational table is said to be in First  Normal Form  (  1NF )  if  it  satisfy the following criterion  :

1.  Each field  (  Intersection of  column  and row  )  can  have only one single value (  Atomic value  )  and  multiple vales are not allowed .

2.   Each relational table   Column ( Attribute ) should have unique name and repeating column groups creates redundant data  and  therefore  not  allowed .

3.  Each  Row  should  have  key Attribute  ( PK ). So that each record can be uniquely identified with reference to key attribute ( Primary Key ) .

Relational Database Normalization 1NF
Relational Database Normalization First Normal Form 1NF

Database Normalization

Second Normal Form ( 2NF )

The  Relational Table is said to be in Second  Normal Form  (  2NF )  if  it  satisfy  the following Conditions  :

  1. First , the  table  must be in  the  First Normal Form ( 1NF  ) . That is table must fulfill all the criterion for First Normal Form ( 1NF ).

2.  All  Non-key attributes ( Column C, D, E, F ) must be totally dependent on the  primary key ( AB )  and  Not  just on one of the prime  attributes ( either A  or  B ).

In Second Normal  Form  ( 2NF )  , The  partial dependencies are  moved  to a   separate  table .

The  partial  dependency can occur only if the primary key  is  a composite key.

Relational Database Normalization 2NF
Relational Database Normalization Second Normal Form 2NF

Database Normalization

Third Normal Form ( 3NF )

The  Relational Table is said to be in Third  Normal Form  (  3NF )  if  it  satisfy  the following Conditions  :

1.  The  table  must be in  the  Second Normal Form  (  2NF )  and  First Normal Form (  1NF ). That is table must fulfill all the criterion for First Normal Form ( 1NF ) And Second Normal Form ( 2NF ).

2. Remove  all  Transitive Dependencies

If  one non key attribute ( C )   determines another non key attribute ( D ) then transitive dependency exist .

The 3NF criterion can be achieved by moving  all  transitively  dependent attributes  to a new separate  table  to  avoid  database anomalies due to transitive  dependencies .

Relational Database Normalization 3NF
Relational Database Normalization Third Normal Form 3NF

Relational Database

Database Normalization

What Is Transitive Dependency ?

A  transitive dependency is defined as If  one non key attribute ( C )   determines another non key attribute ( D ) then transitive dependency exists  in a table .

A functional dependency is said to be transitive dependency  when one non key attribute  determines another non key attribute .

Transitive Functional Dependency
Transitive Functional Dependency

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