Chapter 1: Introduction

Database System Concepts, 7th Ed.

©Silberschatz, Korth and Sudarshan
See www.db-book.com for conditions on re-use
 Database Applications Examples

§ 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

Database System Concepts - 7th Edition 1.4 ©Silberschatz, Korth and Sudarshan
 Database Applications Examples (Cont.)

§ Airlines: reservations, schedules

§ Telecommunication: records of calls, texts, and data usage, generating
monthly bills, maintaining balances on prepaid calling cards
§ Web-based services
• Online retailers: order tracking, customized recommendations
• Online advertisements
§ Document databases
§ Navigation systems: For maintaining the locations of varies places of
interest along with the exact routes of roads, train systems, buses, etc.

Database System Concepts - 7th Edition 1.5 ©Silberschatz, Korth and Sudarshan
 Purpose of Database Systems

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 induplication 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
§ 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

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 Purpose of Database Systems (Cont.)

§ 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
§ Concurrent access by multiple users
• 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
§ Security problems
• Hard to provide user access to some, but not all, data

Database systems offer solutions to all the above problems

Database System Concepts - 7th Edition 1.7 ©Silberschatz, Korth and Sudarshan
 Data Models

§ A collection of tools for describing

• Data
• Data relationships
• Data semantics
• Data constraints
§ Relational model
§ Entity-Relationship data model (mainly for database design)
§ Object-based data models (Object-oriented and Object-relational)
§ Semi-structured data model (XML)
§ Other older models:
• Network model
• Hierarchical model

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 Relational Model

§ All the data is stored in various tables.

§ Example of tabular data in the relational model

Columns

Rows

Ted Codd
Turing Award 1981

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 A Sample Relational Database

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 View of Data

An architecture for a database system

view level

view 1 view 2 … view n

logical
level

physical
level

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 Instances and Schemas

§ Similar to types and variables in programming languages

§ Logical Schema – the overall logical structure of the database
• Example: The database consists of information about a set of
customers and accounts in a bank and the relationship between them
§ Analogous to type information of a variable in a program
§ Physical schema – the overall physical structure of the database
§ Instance – the actual content of the database at a particular point in time
• Analogous to the value of a variable

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 Physical Data Independence

§ 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.

Database System Concepts - 7th Edition 1.16 ©Silberschatz, Korth and Sudarshan
 Data Definition Language (DDL)

§ Specification notation for defining the database schema

Example: create table instructor (
ID char(5),
name varchar(20),
dept_name varchar(20),
salary numeric(8,2))
§ DDL compiler generates a set of table templates stored in a data
dictionary
§ Data dictionary contains metadata (i.e., data about data)
• Database schema
• Integrity constraints
§ Primary key (ID uniquely identifies instructors)
• Authorization
§ Who can access what

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 Data Manipulation Language (DML)

§ Language for accessing and updating the data organized by the

appropriate data model
• DML also known as query language
§ There are basically two types of data-manipulation language
• Procedural DML -- require a user to specify what data are needed
and how to get those data.
• Declarative DML -- require a user to specify what data are needed
without specifying how to get those data.
§ Declarative DMLs are usually easier to learn and use than are procedural
DMLs.
§ Declarative DMLs are also referred to as non-procedural DMLs
§ The portion of a DML that involves information retrieval is called a query
language.

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 SQL Query Language

§ SQL query language is nonprocedural. A query takes as input several

tables (possibly only one) and always returns a single table.
§ Example to find all instructors in Comp. Sci. dept
select name
from instructor
where dept_name = 'Comp. Sci.'
§ SQL is NOT a Turing machine equivalent language
§ To be able to compute complex functions SQL is usually embedded in
some higher-level language
§ 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

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 Database Access from Application Program

§ Non-procedural query languages such as SQL are not as powerful as a

universal Turing machine.
§ SQL does not support actions such as input from users, output to
displays, or communication over the network.
§ Such computations and actions must be written in a host language, such
as C/C++, Java or Python, with embedded SQL queries that access the
data in the database.
§ Application programs -- are programs that are used to interact with the
database in this fashion.

Database System Concepts - 7th Edition 1.20 ©Silberschatz, Korth and Sudarshan
 Database Design

The process of designing the general structure of the database:

§ Logical Design – Deciding on the database schema. Database design

requires that we find a “good” collection of relation schemas.
• Business decision – What attributes should we record in the
database?
• Computer Science decision – What relation schemas should we
have and how should the attributes be distributed among the
various relation schemas?
§ Physical Design – Deciding on the physical layout of the database

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 Database Engine

§ A database system is partitioned into modules that deal with each of the
responsibilities of the overall system.
§ The functional components of a database system can be divided into
• The storage manager,
• The query processor component,
• The transaction management component.

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 Storage Manager
§ 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 OS file manager
• Efficient storing, retrieving and updating of data
§ The storage manager components include:
• Authorization and integrity manager
• Transaction manager
• File manager
• Buffer manager

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 Storage Manager (Cont.)

§ The storage manager implements several data structures as part of the

physical system implementation:
• Data files -- store the database itself
• Data dictionary -- stores metadata about the structure of the
database, in particular the schema of the database.
• Indices -- can provide fast access to data items. A database index
provides pointers to those data items that hold a particular value.

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 Query Processor

§ The query processor components include:

• DDL interpreter -- interprets DDL statements and records the
definitions in the data dictionary.
• DML compiler -- translates DML statements in a query language into
an evaluation plan consisting of low-level instructions that the query
evaluation engine understands.
§ The DML compiler performs query optimization; that is, it picks
the lowest cost evaluation plan from among the various
alternatives.
• Query evaluation engine -- executes low-level instructions generated
by the DML compiler.

Database System Concepts - 7th Edition 1.25 ©Silberschatz, Korth and Sudarshan
 Query Processing

1. Parsing and translation

2. Optimization
3. Evaluation

parser and relational-algebra

query
translator expression

optimizer

query
evaluation engine execution plan
output

data statistics
about data

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 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.

Database System Concepts - 7th Edition 1.27 ©Silberschatz, Korth and Sudarshan
 Database Architecture

§ Centralized databases
• One to a few cores, shared memory
§ Client-server,
• One server machine executes work on behalf of multiple client
machines.
§ Parallel databases
• Many core shared memory
• Shared disk
• Shared nothing
§ Distributed databases
• Geographical distribution
• Schema/data heterogeneity

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 Database Architecture
(Centralized/Shared-Memory)

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 Database Applications

Database applications are usually partitioned into two or three parts

§ Two-tier architecture -- the application resides at the client machine,
where it invokes database system functionality at the server machine
§ Three-tier architecture -- the client machine acts as a front end and
does not contain any direct database calls.
• The client end communicates with an application server, usually
through a forms interface.
• The application server in turn communicates with a database
system to access data.

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 Two-tier and three-tier architectures

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 Database Users

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 Database Administrator

A person who has central control over the system is called a database
administrator (DBA). Functions of a DBA include:
§ Schema definition
§ Storage structure and access-method definition
§ Schema and physical-organization modification
§ Granting of authorization for data access
§ Routine maintenance
§ Periodically backing up the database
§ Ensuring that enough free disk space is available for normal
operations, and upgrading disk space as required
§ Monitoring jobs running on the database

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 History of Database Systems

§ 1950s and early 1960s:

• Data processing using magnetic tapes for storage
§ Tapes provided only sequential access
• Punched cards for input
§ Late 1960s and 1970s:
• Hard disks allowed direct access to data
• Network and hierarchical data models in widespread use
• Ted Codd defines the relational data model
§ Would win the ACM Turing Award for this work
§ IBM Research begins System R prototype
§ UC Berkeley (Michael Stonebraker) begins Ingres prototype
§ Oracle releases first commercial relational database
• High-performance (for the era) transaction processing

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 History of Database Systems (Cont.)

§ 1980s:
• Research relational prototypes evolve into commercial systems
SQL becomes industrial standard
§
• Parallel and distributed database systems
Wisconsin, IBM, Teradata
§
• Object-oriented database systems
§ 1990s:
• Large decision support and data-mining applications
• Large multi-terabyte data warehouses
• Emergence of Web commerce

Database System Concepts - 7th Edition 1.35 ©Silberschatz, Korth and Sudarshan
 History of Database Systems (Cont.)

§ 2000s
• Big data storage systems
§ Google BigTable, Yahoo PNuts, Amazon,
§ “NoSQL” systems.
• Big data analysis: beyond SQL
§ Map reduce and friends
§ 2010s
• SQL reloaded
§ SQL front end to Map Reduce systems
§ Massively parallel database systems
§ Multi-core main-memory databases

Database System Concepts - 7th Edition 1.36 ©Silberschatz, Korth and Sudarshan
 End of Chapter 1

Database System Concepts - 7th Edition 1.37 ©Silberschatz, Korth and Sudarshan