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1. Chapter 1
DBMS Concepts, terminology
and Architecture

2. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
 Database : A collection (or list) of information. A
database is comprised of one or more lists (called
tables) of data organized by columns, rows , and cells.
 Tables : the view that displays the data base as a
combinations of rows (records) and columns (fields).
The cells contain the bits and pieces of data for each
record in each field. The first row of a table is
reserved for the field names.
DBMS terminology

3. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
 Field names : Identify the different categories in a
database. The top row is reserved for field names.
Examples of field names are First name, last name,
address, city, state, zip, phone number.
 Field : Categories in a database. Fields are displayed
in columns. For Example, in a database, the zip field
contains all the zip codes from each of the records.
These are the bits and pieces of data.
DBMS terminology

4. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
 Records: Related information that is separated by
columns or fields. A name and address are considered
one record in the database. A second Name and
address are a different record.
 Cells : the intersection of columns and rows that
contain the data for each record
 Data : all of the records of information in a database
including the field names. Data + Field
Names = Records
All Records = a Database.
DBMS terminology

5. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
 Objects: enables you to find, view, display, and print
data differently, based on your needs. The most
commonly used objects are tables, queries, forms and
reports.
 Tables show all records in a spreadsheet format
 Queries allow you to ask questions of the one or more
tables and show only the information you ask for
 Forms display one record at a time
 Reports give and organize why of presenting
information.
DBMS terminology

6. Copyright © 2011 Ramez Elmasri and Shamkant Navathe

7. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
 Data base Instance:
The term instance is typically used to describe a complete
database environment, including the RDBMS software,
table structure, stored procedures and other functionality.
It is most commonly used when administrators describe
multiple instances of the same database. Also Known As:
environment
Instance and schema

8. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
Data base Instance Example:
An organization with an employees database might have
three different instances:
1. Production (used to contain live data),
2. Pre-production (used to test new functionality prior to
release into production) ,
3. Development (used by database developers to create
new functionality).
Instance and schema

9. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
 Schema:
A relation schema can be thought of as the basic
information describing a table or relation. This includes a
set of column names, the data types associated with each
column, and the name associated with the entire table.
Instance and schema

10. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
Schemas, Instances, and
Database State
 Database schema
 Description of a database
 Schema diagram
 Displays selected aspects of schema
 Schema construct
 Each object in the schema
 Database state or snapshot
 Data in database at a particular moment in time

11. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
Schemas, Instances, and
Database State (cont'd.)
 Define a new database
 Specify database schema to the DBMS
 Initial state
 Populated or loaded with the initial data
 Valid state
 Satisfies the structure and constraints specified in
the schema

12. Data Models, Schemas, and
Instances
 Data model
 Collection of concepts that describe the structure of
a database
 Provides means to achieve data abstraction
 Basic operations
• Specify retrievals and updates on the database
 Dynamic aspect or behavior of a database
application
• Allows the database designer to specify a set of valid
operations allowed on database objects

13. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
Schemas, Instances, and
Database State (cont'd.)
 Schema evolution
 Changes applied to schema as application
requirements change

14. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
Slide 2- 14
Database Schema
vs. Database State (continued)
 Distinction
 The database schema changes very infrequently.
 The database state changes every time the database
is updated.
 Schema is also called intension.
 State is also called extension.

15. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
Three-Schema Architecture
and Data Independence
 Internal level
 Describes physical storage structure of the database
 Conceptual level
 Describes structure of the whole database for a
community of users
 External or view level
 Describes part of the database that a particular user
group is interested in

16. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
Data Independence
 Capacity to change the schema at one level of a
database system
 Without having to change the schema at the next
higher level
 Types:
 Logical
 Physical

17. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
Slide 2- 17
Data Independence
 Logical Data Independence:
 The capacity to change the conceptual schema
without having to change the external schemas and
their associated application programs.
 Physical Data Independence:
 The capacity to change the internal schema without
having to change the conceptual schema.
 For example, the internal schema may be changed
when certain file structures are reorganized or new
indexes are created to improve database
performance

18. Categories of Data Models
 High-level or conceptual data models
 Close to the way many users perceive data
 Low-level or physical data models
 Describe the details of how data is stored on
computer storage media
 Representational data models
 Easily understood by end users
 Also similar to how data organized in computer
storage

19. High-level or conceptual data model
 Entity
 Represents a real-world object or concept
 Attribute
 Represents some property of interest
 Further describes an entity
 Relationship among two or more entities
 Represents an association among the entities
 Entity-Relationship model

20. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
Physical data model
 Describes how data is stored in the computer.
 It represents info such as
- record formats
- record orderings
- access path: make search more efficient

21. Copyright © 2011 Ramez Elmasri and Shamkant Navathe
Representational data model
 Used in traditional commercial DMBS
 They include
- Relational Data model
- Network model
- Hierarchical model

22. Categories of Data Models
(cont'd.)
 Relational data model
 Used most frequently in traditional commercial
DBMSs
 Object data model
 New family of higher-level implementation data
models
 Closer to conceptual data models

23. Categories of Data Models
(cont'd.)
 Physical data models
 Describe how data is stored as files in the computer
 Access path
• Structure that makes the search for particular database
records efficient
 Index
• Example of an access path
• Allows direct access to data using an index term or a
keyword

24. DBMS Languages
 Data definition language (DDL)
• Defines both schemas
 Data manipulation language (DML)
• Allows retrieval, insertion, deletion, modification

25. DBMS Languages (cont'd.)
 High-level or nonprocedural DML
• Can be used on its own to specify complex database
operations concisely
• Set-at-a-time or set-oriented
 Low-level or procedural DML
• Must be embedded in a general-purpose
programming language
• Record-at-a-time
 The “Impedance Mismatch”