DBMS.pdf

Topic for the class:
Unit -I : Basic Concepts of DBMS
Date & Time : 03/01/2023
Mr. Dasari Prasad
Faculty-CSE
NIT- Andhra Pradesh
Tadepalligudem – 534102
Email: prasad.dasari1126@gmail.com
1
Department of CSE , NIT-AP Course Title: DBMS
10 January 2023

What is Data?
• Data became an essential part of
human life.
•Data is nothing but any facts recorded
in our computer.
•Data may consists of Text, numbers,
image ,video, Audio etc.
10 January 2023 Department of CSE , NIT-AP Course Title: DBMS 2

What is Database?
•Database is nothing but Collection of
related data.
• related means Storing data about a
particular subject/topic/things.

What is DBMS?
•DBMS =Database+(Set of programs to
Manage data in the Database)
• Basically DBMS is a Software which
facilitate the storing the data and
applying operations such as retrieving,
Modifying, updating the Database.

What is DBMS?
•DBMS reduce the burden on the OS.
• Examples of DBMS
▪MS Access, MS SQL Server By Microsoft
▪Oracle(Licensed), MySQL(Open Source)
By Oracle

Database Applications
•Enterprise Information
•Sales: customers, products, purchases
•Accounting: payments, receipts, assets
•Human Resources: Information about
employees, salaries, payroll taxes.
•Manufacturing: management of production,
inventory, orders, supply chain.

• Banking and finance
• customer information, accounts, loans, and
banking transactions.
• Credit card transactions
• Finance: sales and purchases of financial
instruments (e.g., stocks and bonds; storing real-
time market data
• Universities: registration, grades

•Airlines: reservations, schedules
•Telecommunication: records of calls, texts, and
data usage, generating monthly bills,
maintaining balances on prepaid calling card.
•Navigation systems: For maintaining the
locations of varies places of interest along with
the exact routes of roads, train systems, buses,
etc.

Purpose of Databases (Limitations with File
System)
• In the early days, database applications were built directly
on top of file systems, which leads to:
• Data redundancy and inconsistency: data is stored in
multiple file formats resulting in duplication of
information in different files.
• Difficulty in accessing data
• Need to write a new program to carry out each new
task to access the data from file system.
• Data isolation
• Data is alone scattered across multiple files

Purpose of Databases(Limitations
with File System)
• Integrity problems
• Integrity constraints (e.g., account balance > 0) become
“buried” in program code rather than being stated
explicitly.
• Hard to add new constraints or change existing ones
• Atomicity of updates
• Failures may leave database in an inconsistent state with
partial updates carried out
• Example: Transfer of funds from one account to another
should either complete or not happen at all

Purpose of Databases(Limitations
with File System)
▪Concurrent access needed for performance
• Uncontrolled concurrent accesses can lead to
inconsistencies
• Ex: Two people reading a balance (say 100) and
updating it by withdrawing money (say 50 each) at the
same time
• Data Security
• Hard to provide user access to some, but not all data

Advantages with DBMS
•Data Redundancy is reduced or
eliminated in DBMS because all data
are stored at a centralized location
rather than being created by individual
users and for each application..
• Data Replication is allowed

•Data Concurrency
•In DBMS, Data are stored in one or more
servers in the network and that there is
some software locking mechanism that
prevents the same set of data from being
changed by two people at the same time.

• Data Inconsistency
•In traditional file system storage, the changes
made by one user in one application doesn’t
update the changes in other application, given
both have the same set of details. While this is
not the case with DBMS systems as there is a
single repository of data that is defined once
and is accessed by many users, and data are
consistent.

•Data Integration
•Data integration is a process of combining
the data residing at different locations
and present the user with a unified view
of data. DBMS systems allow Data
Integration with much feasibility.

•Data Access
•While in traditional file-based approach, it might
take hours to look for very specific information
that might be needed in the context of some
business emergency, while DBMS reduces this
time to a few seconds. This is a great advantage
of DBMS because we can write small queries
which will search the Database for you and it
will retrieve the information in the fastest way
possible due to its inbuilt searching operations.

•Data Backup and Recovery
•This is another advantage of DBMS as it
provides a strong framework for Data backup,
users are not required to back up their data
periodically and manually, it is automatically
taken care by DBMS. Moreover, in case of a
server crash, DBMS restores the Database to
its previous condition.

•Data Atomicity
•An atomic transaction is one in which all
of the database actions occur or none of
them do. It is the duty of DBMS to store a
complete transaction in the database. If
any transaction is partially completed,
then it rolls backs them.

•Data Security
•DBMS systems provide a strong
framework to protect data privacy and
security. DBMS ensures that only
authorized users have access to data and
there is a mechanism to define access
privileges.

•Reduced Application Development
Time

Databases based on type of data
Examples
▪Traditional Databases
▪Multimedia databases
▪ GIS Database
▪Real time Databases

Data Model
•Data Model is nothing but it is a
representation of data in the database in a
specific Manner.
▪Data Models are used to show how data is
stored, connected, accessed and updated
in the database management system

Hierarchical Data Model
• Hierarchical Model was the first DBMS model. This model
organizes the data in the hierarchical tree structure.
• The hierarchy starts from the root which has root data and
then it expands in the form of a tree adding child node to the
parent node.
• Ex: IMS(IBM Information
Management System)

Network Data Model
• This model is an extension of the hierarchical model. It was
the most popular model before the relational model.
• This model is the same as the hierarchical model, the only
difference is that a record can have more than one parent. It
replaces the hierarchical tree with a graph.
• Ex: IDS(Integrated Data Store)
• It is an Early Network DB

Object-oriented Data Model
• The real-world problems are more closely represented
through the object-oriented data model.
• In this model, both the data and relationship are
present in a single structure known as an object

Entity-Relationship(E-R) Data Model
• simply ER Model is a high-level data model diagram. In this
model, we represent the real-world problem in the pictorial
form to make it easy for the stakeholders to understand.

Relational Data Model
• Relational Model is the most widely used model. In this
model, the data is maintained in the form of a two-
dimensional table.
• All the information is stored in the form of row and
columns.
• The basic structure of a relational model is tables. So,
the tables are also called relations in the relational
model.

Relational Data Model

Types of Databases based on Data
Model
▪Hierarchical Databases
▪Network Databases
▪Object-Oriented Databases
▪Relational Databases
▪Cloud Databases

Databases based on database Schema
1. Structured Databases(SQL
Databases) ---uses Relational data
model
Ex: Oracle, MySQL ,MS SQL Server
2. Unstructured Databases(NoSQL
Databases)
Ex: MongoDB , CouchDB, Cassandra etc

Database Languages
• Language used to communicate with Database ---
SQL
• SQL(Structured Query Language) is a query
language to access databases.
• SQL have 4 components
1.DDL (Data Definition Language)
2.DML (Data Manipulation Language)
3. DCL (Data Control Language)
4. TCL (Transaction Control Language)

DDL(Data Definition Language)
•Data Definition Language (DDL) is a set of
special Database commands that allows us
to Create or define database and modify
the structure and the metadata of the
database.
• These commands can be used to create,
modify, and delete the database structures
such as schema, tables etc.

Database Commands that comes under DDL are C,A,D
C- Create
A- Alter
D- Drop
Create COMMAND: used to create database table along with its
schema(Structure of database)
Syntax:
Create table <table-name>(Attribute1 datatype,Attribute2
datatype,……..,AttributeN data type, Integrity Constraints1,2…N);

Ex:
Create table student(name varchar(20),roll int(10),marks int(10));

Alter Command: used to change the Database schema
Syntax:
❖ Adding the column to the Table
1.alter table <table-name> add <column-name>
<data-type>;
❖ Deleting the Column from the table
2. alter table <table-name> drop COLUMN <column-
name>;

Alter Command: used to change the Database schema
❖ TO Rename the Column of the Table
3. Alter table <table-name> rename COLUMN <old-
Column-name> to <new-Column-name>;
❖ TO Change the datatype of the column
4. Alter table <table-name> modify COLUMN <column-
name> <new-datatype>

DROP Command: used to Completely delete the
Structure of the table and its data.
Syntax:
drop table <table-name>;
Ex:
Drop table student;

DML(Data Manipulation Language)
• DDL do changes to the Structure of the table where
as DML works on data inside the table includes data
insert , delete, update and retrieve the data.
• Database commands comes under DML are S,I,D,U
S-Select
I- Insert
D- Delete
U- Update

Select Command: is used to Retrieve the Data from
the data base
Syntax:
❖Select [attribute1,attribute2… or *] from <table-
name>;
❖Select [attribute1,attribute2… or *] from <table-
name> where <condition>
Ex: select sname from student;
select * from student;
select * from student where roll=10

Insert Command: used to place the data into the database
table.
Syntax:
❖insert into <table-name> values(value1,value2,…);
❖Insert into <table-name>(column1,2,…) values(value1,2,3….)
Ex: insert into student values(‘Prasad’,10,’CSE’,’NIT-AP’);
insert into student(name,roll) values(‘prasad’,10);

Delete Command: used to delete the records of the database
table based on condition but not delete table structure.
Syntax:
❖delete from <table-name>; //to delete all records
❖delete from <table-name> where <condition>; //delete specific
Ex:
delete from student;
delete from student where roll=10; //delete specific

Update Command: used to replace any data in the database
table.
Syntax:
//To update specific record
❖update <table-name> SET A1=V1,A2=V2….where <condition>;
❖update <table-name> SET A1=V1,A2=V2;//To update all
records
Note: A1,A2,…. Are Attributes and V1,V2,….. Are Values
Ex: update student SET marks=70 where roll=10;
update student SET marks=70;

Views of database

Views of database
• A major purpose of a database system is to provide users with
an abstract view of the data. That is, the system hides certain
details of how the data are stored and maintained.
• Physical level. The lowest level of abstraction describes how
the data are actually stored. The physical level describes
complex low-level data structures in detail.
• Logical level. The next-higher level of abstraction describes
what data are stored in the database, and what relationships
exist among those data.

Views of database
• View level: The highest level of abstraction describes only part of
the entire database. Many users of the database system do not
need all this information; instead, they need to access only a part of
the database.
• The system may provide many views for the same database.
• Database systems have several schemas, partitioned according to
the levels of abstraction. The physical schema describes the
database design at the physical level, while the logical schema
describes the database design at the logical level. A database may
also have several schemas at the view level, sometimes called
subschemas or External schema, that describe different views of
the database

Data independence

Data Independence
Physical Data Independence :
• Physical Data Independence is defined as the ability to make
changes in the structure of the lowest level of the DBMS without
affecting the higher-level schemas. Hence, modification in the
Physical level should not result in any changes in the Logical or View
levels.
Logical Data Independence
• Logical Data Independence is defined as the ability to make changes
in the structure of the middle level of the DBMS without affecting
the highest-level schema or application programs. Hence,
modification in the logical level should not result in any changes in
the view levels or application programs.

Database Design
• The database design process can be divided into six steps.
• The ER model is most relevant to the first three steps.
1. Requirements Analysis: The very first step in designing a
database application is to understand what data is to be stored
in the database, what applications must be built on top of it, and
what operations are most frequent and subject to performance
requirements.
2. Conceptual Database Design: The information gathered in the
requirements analysis step is used to develop a high-level
description of the data to be stored in the database, along with
the constraints known to hold over this data. This step is often
carried out using the E-R(Entity-Relationship) model.

Database Design
3. Logical Database Design: We must choose a DBMS to
implement our database design, and convert the conceptual
database design into a database schema in the data model of
the chosen DBMS.
4. Schema Refinement: T to analyze the collection of relations in
our relational database schema to identify potential problems,
and to refine it. We will use Normalization to refine database
schema to avoid data redundancy.
5. Physical Database Design: Specifies how database tables
exactly stores in the physical memory i.e collection of files stores
as sequence of bytes. This step may simply involve building
indexes on some tables and clustering some tables, to ensure
that it meets desired performance criteria.

Database Design
6. Application and Security Design: Any software project that
involves a DBMS must consider aspects of the application that
go beyond the database itself. For each user, we must identify
the parts of the database that must be accessible and the parts
of the database that must not be accessible, and we must take
steps to ensure that these access rules are enforced.

DBMS Architecture

DBMS Architecture
Database Users and User Interfaces
• There are four different types of database-system users,
differentiated by the way they expect to interact with the
system. Different types of user interfaces have been designed
for the different types of users. • Naive users : are
unsophisticated users who interact with the system by invoking
one of the application programs that have been written
previously.
• For example, a clerk in the university who needs to add a new
instructor to department A invokes a program called new hire.
This program asks the clerk for the name of the new instructor,
her new ID, the name of the department (that is, A), and the
salary.

DBMS Architecture
• Application programmers: are computer professionals who write
application programs. Application programmers can choose from many
tools to develop user interfaces.
• Sophisticated users interact: with the system without writing programs.
Instead, they form their requests either using a database query language
or by using tools such as data analysis software. Analysts who submit
queries to explore data in the database fall in this category.
• Database Administrator: One of the main reasons for using DBMSs is to
have central control of both the data and the programs that access those
data. A person who has such central control over the system is called a
database administrator (DBA).
• The functions of a DBA include:
• Schema definition. The DBA creates the original database schema
• Storage structure and access-method definition.
• Granting of authorization for data access

DBMS Architecture
The Query Processor
The query processor components include:
• DDL interpreter, which interprets DDL statements and records the
definitions in the data dictionary.
• DML compiler, which translates DML statements in a query
language into an evaluation plan consisting of low-level instructions
that the query evaluation engine understands. A query can usually
be translated into any of a number of alternative evaluation plans
that all give the same result. The DML compiler also performs query
optimization; that is, it picks the lowest cost evaluation plan from
among the alternatives.
• Query evaluation engine: which executes low-level instructions
generated by the DML compiler

DBMS Architecture
Storage Manager
• The storage manager is the component of a database system
that provides the interface between the low-level data stored
in the database and the application programs and queries
submitted to the system.
• The storage manager is responsible for the interaction with the
file manager. The raw data are stored on the disk using the file
system provided by the operating system.
• The storage manager translates the various DML statements
into low-level file-system commands. Thus, the storage
manager is responsible for storing, retrieving, and updating
data in the database.

DBMS Architecture
The storage manager components include:
• Authorization and integrity manager, which tests for the
satisfaction of integrity constraints and checks the authority of
users to access data.
• Transaction manager, which ensures that the database
remains in a consistent (correct) state despite system failures,
and that concurrent transaction executions proceed without
conflicting.
• File manager, which manages the allocation of space on disk
storage and the data structures used to represent information
stored on disk.

DBMS Architecture
• Buffer manager, which is responsible for fetching data from disk
storage into main memory, and deciding what data to cache in main
memory.
The buffer manager is a critical part of the database system, since it
enables the database to handle data sizes that are much larger than
the size of main memory.
The storage manager implements several data structures as part of
the physical system implementation:
• Data files, which store the database itself.
• Data dictionary, which stores metadata about the structure of the
database, in particular the schema of the database.
• Indices, which can provide fast access to data items. Like the index
in this textbook,

History of Databases
• 1950s and early 1960s: Magnetic tapes were developed for data storage.
• Late 1960s and 1970s: Widespread use of hard disks in the late 1960s changed the
scenario for data processing greatly, since hard disks allowed direct access to data.
• Charles Bachman was the first person to develop the Integrated Data Store (IDS) which
was based on network data model for which he was inaugurated with the Turing Award
(The most prestigious award which is equivalent to Nobel prize in the field of Computer
Science.). It was developed in early 1960’s.
• In the late 1960’s, IBM (International Business Machines Corporation) developed the
Integrated Management System. It was developed based on the hierarchical database
model. IBM Db2 also released which is RDBMS.
• It was during the year 1970 that the relational database model was developed by Edgar
F.Codd. Many of the database models we use today are relational based. It was
considered the standardized database model from then

History of Databases
• By the early 1980s, relational databases had become competitive with network and
hierarchical database systems even in the area of performance. Relational databases
were so easy to use that they eventually replaced network and hierarchical databases;
• The relational model was still in use by many people in the market.Later during the same
decade (1980’s), IBM developed the Structured Query Language (SQL) as a part of R
project. It was declared as a standard language for the queries by ISO and ANSI. The
Transaction Management Systems for processing transactions was also developed by
James Gray for which he was felicitated the Turing Award.
• 1990s: The major event of the 1990s was the explosive growth of the World WideWeb.
Databases were deployed much more extensively than ever before.

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