1. Database Management Systems

2. TEXT BOOKS
1. Database Management Systems, Raghurama Krishnan, Johannes Gehrke, TATA McGrawHill 3rd edition
2. Database System Concepts, Silberschatz, Korth, McGraw hill, 5 th edition.
REFERENCES :
1. Database Systems design, Implementation, and Management, Peter Rob & Carlos Coronel 7 th Edition.
2. Fundamentals of Database Systems, Elmasri Navate, Pearson Education
3. Introduction to Database Systems, C.J.Date, Pearson Education

3. Chapter 1: Introduction
Purpose of Database Systems
View of Data
Data Models
Data Definition Language
Data Manipulation Language
Transaction Management
Storage Management
Database Administrator
Database Users
Overall System Structure

4. Database Management System (DBMS)
Collection of interrelated data
Set of programs to access the data
DBMS contains information about a particular enterprise
DBMS provides an environment that is both convenient and efficient to use.
Database Applications:
Banking: all transactions
Airlines: reservations, schedules
Universities: registration, grades
Sales: customers, products, purchases
Manufacturing: production, inventory, orders, supply chain
Human resources: employee records, salaries, tax deductions
Databases touch all aspects of our lives

5. Some Issues Creation of definitions/structures Storing
Various views
Various types of users
Storing
Retrieving -- Indexes
Manipulating the data
Designing a good database --Normalization
Support for transactions
Crash recovery
Concurrent execution
Two clerks trying to reserve the same berth in a railway reservation system!
Two concurrent programs trying to add Rs 50 and Rs 100 to the same account.
Security

6. Purpose of Database System
In the early days, database applications were built on top of file systems
Drawbacks of using file systems to store data:
Data redundancy and inconsistency
Multiple file formats, duplication of information in different files
Difficulty in accessing data
Need to write a new program to carry out each new task
Data isolation — multiple files and formats.
It should be possible for you to write your program without worrying about other programs. Thinks that you alone is using the data.
Integrity problems
Integrity constraints (e.g. account balance > 0) become part of program code
Hard to add new constraints or change existing ones

7. Purpose of Database Systems (Cont.)
Drawbacks of using file systems (cont.)
Atomicity of updates
Failures may leave database in an inconsistent state with partial updates carried out
E.g. transfer of funds from one account to another should either complete or not happen at all
Concurrent access by multiple users
Concurrent accessed needed for performance
Uncontrolled concurrent accesses can lead to inconsistencies
E.g. two people reading a balance and updating it at the same time
Security problems
Database systems offer solutions to all the above problems

8. Levels of Abstraction
Physical level describes how a record (e.g., customer) is stored.
Logical level: describes data stored in database, and the relationships among the data.
There are customers and accounts. Relationship is a customer can have one or many accounts.
Similarly a constraint saying that account-balance is non-negative is also part of the logical level description.
View level: There are several categories of users of a DBMS. They want to see the data in a particular form because of ease or clarity. Sometimes only part of a database is allowed to be accessed by a particular user.
There is only one Physical and Logical level schema, but there can be many view level schemas.

9. An architecture for a database system
View of Data
An architecture for a database system

10. Instances and Schemas
Similar to types and variables in programming languages
Schema – the description about the data -- Meta data (data about data)
Schema is also data !
A program which wants to access data, should first access the schema to know the things likes format, type of the data, etc.
This is a powerful concept which allows us to see the data in a more abstract way.
Physical schema: database description at the physical level
Logical schema: database description at the logical level
Instance – the actual content of the database at a particular point in time
Analogous to the value of a variable
Physical Data Independence – the ability to modify the physical schema without changing the logical schema
Applications depend on the logical schema
In general, the interfaces between the various levels and components should be well defined so that changes in some parts do not seriously influence others.

11. Data Models
A collection of conceptual tools for describing data items along with relationship between them. It can also describe other information like constraints, etc.
Entity-Relationship model: A high level conceptual model which can be used to describe an enterprise without worrying about the technicalities of DBMS or any other system.
Good to do the requirements analysis.
Later on this can be converted easily into other models which are more technical.
Relational model: DB is a collection of relations. Relations(tables) are used to describe both data and relationships.
Other models: object-oriented model, semi-structured data models.
Older models: network model and hierarchical model

12. Entity-Relationship Model
An Example: ( we will see in detail later-on)

13. Entity Relationship Model (Cont.)
E-R model of real world
Entities (objects)
E.g. customers, accounts, bank branch
Relationships between entities
E.g. Account A-101 is held by customer Johnson
Relationship set depositor associates customers with accounts
Widely used for database design at a very high abstract level
Database design in E-R model usually converted to design in the relational model (coming up next) which is used for storage and processing

14. Relational Model Example of tabular data in the relational model
Attributes
Example of tabular data in the relational model
customer-
name
customer-
street
customer-
city
account-
number
Customer-id
Johnson
Smith
Jones
Alma
North
Main
Palo Alto
Rye
Harrison
A-101
A-215
A-201
A-217

15. A Sample Relational Database

16. DDL and DML
Language for accessing and manipulating the data organized by the appropriate data model
DML also known as query language
Two classes of languages
Procedural – user specifies what data is required and how to get those data
Nonprocedural – user specifies what data is required without specifying how to get those data
SQL is the most widely used query language

17. DDL and DML : SQL
Data definition language is used to define schema (mostly at logical level) of a relation.
E.g. create table account ( account-number char(10), balance integer)
DDL compiler generates a table (relation) called account which is ready to be populated.
To insert a row (a data item) into the account table
insert into account
values (‘A-9732’,1200)

18. SQL
SQL: widely used non-procedural language which contains both DDL and DML.
E.g. find the name of the customer with customer-id select customer.customer-name from customer where customer.customer-id = ‘ ’
E.g. find the balances of all accounts held by the customer with customer-id select account.balance from depositor, account where depositor.customer-id = ‘ ’ and depositor.account-number = account.account-number
Application programs generally access databases through one of
Language extensions to allow embedded SQL
Application program interface (e.g. ODBC/JDBC) which allow SQL queries to be sent to a database

19. Database Users
Users are differentiated by the way they expect to interact with the system
Application programmers – Write applications which uses a database. They should know regarding how to access the database by using a host language, etc.
Sophisticated users – form requests in a database query language
Naïve users – Use already developed tools to access the data. E.g. people accessing database over the web, bank tellers, clerical staff

20. Database Administrator
Coordinates all the activities of the database system; the database administrator has a good understanding of the enterprise’s information resources and needs.
Database administrator's duties include:
Schema definition
Storage structure and access method definition
Schema and physical organization modification
Granting user authority to access the database
Specifying integrity constraints
Acting as liaison with users
Monitoring performance and responding to changes in requirements

21. Transaction Management
A transaction is a collection of operations that performs a single logical function in a database application
Transaction-management component ensures that the database remains in a consistent (correct) state despite system failures (e.g., power failures and operating system crashes) and transaction failures.
Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database.

22. Storage Management
Storage manager is a program module 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 to the following tasks:
interaction with the file manager
efficient storing, retrieving and updating of data

23. Overall System Structure

24. Application Architectures
Two-tier architecture: E.g. client programs using ODBC/JDBC to communicate with a database
Three-tier architecture: E.g. web-based applications, and applications built using “middleware”

25. History
It is closely related to the history of storage mediums from punched cards to hard disks; also related to data models from early network or hierarchical model to object oriented models.
1950s and early 1960s: Magnetic tapes, punched cards are used as input medium. Output could be tape or punched card or printer.
Tapes are sequential, often main memory size is for lesser than the tape size. You need to write restricted programs which process at a time only a small quantity of data.
Late 1960s and 1970s: Hard disks. Random access. Allowed data structures to be stored on a disk. Network and hierarchical model of early databases is possible because of this.
A landmark paper by Codd [1970] defined the relational model and non-procedural ways of querying data in the relational model.
Codd won the prestigious Association of Computing Machinery Turing Award.

26. History
1980s: Hierarchical and network models dominated in late 1970s, even though relational model is academically insteresting.
This is because, hierarchical and network models are efficient (speed) than relational models
Situation changed with System R, a ground breaking project at IBM Research that developed techniques for construction of an efficient relational database system.
Initial commercial RDBMS came into picture: IBM DB2, Oracle, Ingres, and DEC Rdb
1980s saw much research on parallel and distributed databases, as well as initial work on object-oriented databases.

27. History Early 1990s: Transaction processing capabilities
Tools for analyzing large amounts of data
Late 1990s: World Wide Web
High transaction processing rates
24X7 working systems – no downtime even for maintenance.
Early 2000s:
XML, XQuery  new database technology.
Data warehousing, data mining tools