DataBaseManagementSystems OVERVIEW and introduction

LEARNİNG OBJECTİVES
Explain why humankind’s interest in data goes back to ancient times.
Describe how data needs have historically driven many information technology
developments.
Describe the evolution of data storage media during the last century.
Relate the idea of data as a corporate resource that can be used to gain a
competitive advantage to the development of the database management systems
environment.
Differentiate the types of databases and database applications
Understand the principals of typical DBMS functionality
Explain the main characteristics of the database approach
Know the types of database users
Appraise the advantages of using the database approach
Summarize the historical development of database technology
Know how to extend database capabilities
Estimate when not to use databases 3

OUTLİNE
Data in history
Data storage media (today and in the past)
Types of Databases and Database Applications
Basic Definitions
Typical DBMS Functionality
Example of a Database (UNIVERSITY)
Main Characteristics of the Database Approach
Types of Database Users
Advantages of Using the Database Approach
Historical Development of Database Technology
Extending Database Capabilities
When Not to Use Databases 4

DATA
Data - the foundation of technological activity
Database - a highly organized collection of assembled
data
Database Management System - sophisticated
software that controls the database and the
database environment
5

WHAT IS DATA?
 A single piece of data is a single fact about
something that interests us.
 A fact can be any characteristic of an object.
6

HISTORY OF DATA
People have been interested in data for at least
the past 12,000 years.
Non-computer, primitive methods of data storage
and handling.
7

WHAT IS DATA? (CONT.)
 Shepherds kept track of their flocks with pebbles.
 A primitive but legitimate example of data storage
and retrieval.
8

HISTORY OF DATA
 Dating back to 8500 B.C., unearthed clay tokens or
“counters” may have been used for record keeping in
primitive forms of accounting.
 Tokens, with special markings on them, were sealed in hollow
clay vessels that accompanied commercial goods in transit.
9

DATA THROUGH THE AGES
Record-keeping - the recording of data to keep
track of how much a person has produced and
what it can be bartered or sold for.
With time, different kinds of data were kept
 calendars, census data, surveys, land ownership
records, marriage records, records of church
contributions, family trees, etc.
10

HISTORY OF DATA
 Double-entry bookkeeping - originated in the
trading centers of fourteenth century Italy.
 The earliest known example is from a merchant in
Genoa and dates to the year 1340.
11

EARLY DATA PROBLEMS SPAWN
CALCULATING DEVICES
People interested in devices that could
“automatically” process their data.
Blaise Pascal produced an adding machine that
was an early version of today’s mechanical
automobile odometers.
12

PUNCHED CARDS - DATA STORAGE
Invented in 1805 by Joseph Marie Jacquard of
France.
Jacquard’s method of storing fabric patterns, a form
of graphic data, as holes in punched cards was a
very clever means of data storage.
Of great importance for computing devices to follow.
13

ERA OF MODERN INFORMATION
PROCESSING
The 1880 U.S. Census took about seven years to compile by
hand.
Basing his work on Jacquard’s punched card concept,
Herman Hollerith arranged to have the census data stored
in punched cards and invented machinery to tabulate them.
In 1896 Hollerith formed the Tabulating Machine Company to
produce and commercially market his devices -- this later
became IBM.
14

ERA OF MODERN INFORMATION
PROCESSING
James Powers developed devices to
automatically feed cards into the equipment
and to automatically print results.
In 1911 he established the Powers Tabulating
Machine Company -- this later became Unisys
Corporation.
15

THE MID-1950S
The introduction of electronic computers.
Witnessed a boom in economic development.
From this point onward, it would be virtually
impossible to tie advances in computing
devices to specific, landmark data storage and
retrieval needs.
16

MODERN DATA STORAGE MEDIA
Punched paper tape - The earliest form of
modern data storage, introduced in the 1870s
and 1880s.
Punched cards were the only data storage
medium used in the increasingly sophisticated
electromechanical accounting machines of the
1920s, 1930s, and 1940s.
17

Middle to late 1930s saw the beginning of the era of
erasable magnetic storage media.
By late 1940s, early work was done on the use of
magnetic tape for recording data.
By 1950, several companies were developing the
magnetic tape concept for commercial use.
18

Magnetic Tape - commercially available units in 1952.
Direct Access Magnetic Devices - began to be developed at MIT
in the late 1930s and early 1940s.
Magnetic Drum - early 1950s; forerunners of magnetic disk
technology.
Magnetic Disk - commercially available in mid 1950s.
Compact Disk (CD) – introduced as a data storage medium in
1985.
Solid-state technology – Flash drives.
19

USING DATA FOR COMPETITIVE ADVANTAGE
Data has become indispensable to every kind of modern business and government
organization.
Data, the applications that process the data, and the computers on which the
applications run are fundamental to every aspect of every kind of endeavor.
20

USING DATA FOR COMPETITIVE ADVANTAGE
Data is a corporate resource, possibly the most important corporate resource.
Data can give a company a crucial competitive advantage.
e.g., FedEx had a significant competitive advantage when it first provided access to its
package tracking data on its Web site.
21

PROBLEMS IN STORING AND ACCESSING
DATA
Difficult to store and to provide efficient, accurate access to a company’s data.
The volume of data that companies have is massive.
Wal-Mart estimates its data warehouse contains hundreds of terabytes (trillions of
characters) of data.
22

PROBLEMS IN STORING AND ACCESSING
DATA
Larger number of people want access to data:
 Employees
 Customers
 Trading partners
Additional issues include: data security, data privacy, and backup and recovery.
23

DATA SECURITY
Involves a company protecting its data from theft, malicious destruction, deliberate
attempts at making phony changes to the data.
e.g., someone trying to increase his own bank account balance.
24

DATA PRIVACY
Ensuring that even employees who normally have access to the company’s data are
given access only to the specific data that they need in their work.
25

BACKUP AND RECOVERY
The ability to reconstruct data if it is lost or corrupted.
e.g., following a hardware failure
e.g., following a natural disaster
26

DATA ACCURACY
The same data is stored several, sometimes many, times within a company’s
information system.
When a new application is written, new data files are created to store its data.
Data can be duplicated within a single file and across files.
27

DATA AS A CORPORATE RESOURCE
Data may be the most difficult corporate resource to manage.
We have tremendous volume, billions, trillions, and more individual pieces of data,
each piece of which is different from the next.
28

DATA AS A CORPORATE RESOURCE
A new kind of software is required to help manage the data.
Progressively faster hardware is required to keep up with the increasing volume of
data and data access demands.
Data management specialists need to be developed and educated.
29

THE DATABASE ENVIRONMENT
Database Management System (DBMS)
New Personnel - database administrator and data management specialist
Fast hardware
Massive data storage facilities
30

Encourages data sharing
Helps control data redundancy
Has important improvements in data accuracy
Permits storage of vast volumes of data with acceptable access.
31

Allows database queries
Provides tools to control:
 data security
 data privacy
 backup and recovery
32

TYPES OF DATABASES AND DATABASE
APPLICATIONS
Traditional Applications:
 Numeric and Textual Databases
More Recent Applications:
 Multimedia Databases
 Geographic Information Systems (GIS)
 Biological and Genome Databases
 Data Warehouses
 Mobile databases
 Real-time and Active Databases
33

RECENT DEVELOPMENTS (CONT.)
Social Networks started capturing a lot of information about people and about
communications among people-posts, tweets, photos, videos in systems such as:
- Facebook
- Twitter
- Linked-In
All of the above constitutes data
Search Engines- Google, Bing, Yahoo : collect their own repository of web pages for
searching purposes
34

RECENT DEVELOPMENTS (CONT.)
New Technologies are emerging from the so-called non-database software vendors to
manage vast amounts of data generated on the web:
Big Data storage systems involving large clusters of distributed computers (Chapter
25)
NOSQL (Not Only SQL) systems (Chapter 24)
A large amount of data now resides on the “cloud” which means it is in huge data
centers using thousands of machines.
35

BASIC DEFINITIONS
Database:
 A collection of related data.
Data:
 Known facts that can be recorded and have an implicit meaning.
Mini-world:
 Some part of the real world about which data is stored in a database. For
example, student grades and transcripts at a university.
Database Management System (DBMS):
 A software package/ system to facilitate the creation and maintenance of a
computerized database.
Database System:
 The DBMS software together with the data itself. Sometimes, the applications
are also included.
36

IMPACT OF DATABASES AND DATABASE
TECHNOLOGY
Businesses: Banking, Insurance, Retail, Transportation, Healthcare, Manufacturing
Service Industries: Financial, Real-estate, Legal, Electronic Commerce, Small
businesses
Education : Resources for content and Delivery
More recently: Social Networks, Environmental and Scientific Applications, Medicine
and Genetics
Personalized Applications: based on smart mobile devices
37

SIMPLIFIED DATABASE SYSTEM
ENVIRONMENT
38

TYPICAL DBMS FUNCTIONALITY
Define a particular database in terms of its data types, structures,
and constraints
Construct or Load the initial database contents on a secondary
storage medium
Manipulating the database:
 Retrieval: Querying, generating reports
 Modification: Insertions, deletions and updates to its content
 Accessing the database through Web applications
Processing and Sharing by a set of concurrent users and
application programs – yet, keeping all data valid and consistent
39

DATABASE MODEL REQUIREMENTS
PQRI:
40
Reactivity
Integrity
Quantity
Persistency
Database model

APPLICATION ACTIVITIES AGAINST A
DATABASE
Applications interact with a database by generating
- Queries: that access different parts of data and formulate the result of a request
- Transactions: that may read some data and “update” certain values or generate new
data and store that in the database
Applications must not allow unauthorized users to access data
Applications must keep up with changing user requirements against the database
41

ADDITIONAL DBMS FUNCTIONALITY
DBMS may additionally provide:
 Protection or Security measures to prevent unauthorized access
 “Active” processing to take internal actions on data
 Presentation and Visualization of data
 Maintenance of the database and associated programs over the lifetime of the
database application
 Called database, software, and system maintenance
42

EXAMPLE OF A DATABASE
(WITH A CONCEPTUAL DATA MODEL)
Mini-world for the example:
 Part of a UNIVERSITY environment.
Some mini-world entities:
 STUDENTs
 COURSEs
 SECTIONs (of COURSEs)
 (academic) DEPARTMENTs
 INSTRUCTORs
43

EXAMPLE OF A DATABASE
(WITH A CONCEPTUAL DATA MODEL) (CONT.)
Some mini-world relationships:
 SECTIONs are of specific COURSEs
 STUDENTs take SECTIONs
 COURSEs have prerequisite COURSEs
 INSTRUCTORs teach SECTIONs
 COURSEs are offered by DEPARTMENTs
 STUDENTs major in DEPARTMENTs
Note: The above entities and relationships are typically expressed in a
conceptual data model, such as the ENTITY-RELATIONSHIP data
model (see Chapters 3, 4)
44

EXAMPLE OF A SIMPLE DATABASE
45

MAIN CHARACTERISTICS OF THE DATABASE
APPROACH
Self-describing nature of a database system:
 A DBMS catalog stores the description of a particular database (e.g. data
structures, types, and constraints)
 The description is called meta-data*.
 This allows the DBMS software to work with different database applications.
Insulation between programs and data:
 Called program-data independence.
 Allows changing data structures and storage organization without having to
change the DBMS access programs.
-----------------------------------------------------------------------------
* Some newer systems such as a few NOSQL systems need no meta-data:
they store the data definition within its structure making it self describing
46

EXAMPLE OF A SIMPLIFIED DATABASE
CATALOG
47

MAIN CHARACTERISTICS OF THE DATABASE APPROACH (CONT.)
Data Abstraction:
 A data model is used to hide storage details and present the users with a
conceptual view of the database.
 Programs refer to the data model constructs rather than data storage details
Support of multiple views of the data:
 Each user may see a different view of the database, which describes only the data
of interest to that user.
48

MAIN CHARACTERISTICS OF THE DATABASE APPROACH (CONT.)
Sharing of data and multi-user transaction processing:
 Allowing a set of concurrent users to retrieve from and to
update the database.
 Concurrency control within the DBMS guarantees that each
transaction is correctly executed or aborted
 Recovery subsystem ensures each completed transaction has
its effect permanently recorded in the database
 OLTP (Online Transaction Processing) is a major part of
database applications. This allows hundreds of concurrent
transactions to execute per second.
49

DATABASE USERS
Users may be divided into
 Those who actually use and control the database content, and those who design,
develop and maintain database applications (called “Actors on the Scene”), and
 Those who design and develop the DBMS software and related tools, and the
computer systems operators (called “Workers Behind the Scene”).
50

DATABASE USERS – ACTORS ON THE SCENE
Actors on the scene
 Database administrators:
 Responsible for authorizing access to the database, for coordinating and
monitoring its use, acquiring software and hardware resources, controlling its
use and monitoring efficiency of operations.
 Database Designers:
 Responsible to define the content, the structure, the constraints, and functions
or transactions against the database. They must communicate with the end-
users and understand their needs.
51

DATABASE END USERS
Actors on the scene (continued)
 End-users: They use the data for queries, reports and some of them update the
database content. End-users can be categorized into:
 Casual: access database occasionally when needed
 Naïve or Parametric: they make up a large section of the end-user population.
 They use previously well-defined functions in the form of “canned
transactions” against the database.
 Users of Mobile Apps mostly fall in this category
 Bank-tellers or reservation clerks are parametric users who do this activity for
an entire shift of operations.
 Social Media Users post and read information from websites
52

DATABASE END USERS (CONT.)
 Sophisticated:
 These include business analysts, scientists, engineers, others thoroughly
familiar with the system capabilities.
 Many use tools in the form of software packages that work closely with the
stored database.
 Stand-alone:
 Mostly maintain personal databases using ready-to-use packaged
applications.
 An example is the user of a tax program that creates its own internal database.
 Another example is a user that maintains a database of personal photos and
videos.
53

DATABASE USERS – ACTORS ON THE SCENE
(CONT.)
 System Analysts and Application Developers
This category currently accounts for a very large proportion of the IT
work force.
System Analysts: They understand the user requirements of naïve and
sophisticated users and design applications including canned transactions to meet
those requirements.
Application Programmers: Implement the specifications developed by
analysts and test and debug them before deployment.
Business Analysts: There is an increasing need for such people who can
analyze vast amounts of business data and real-time data (“Big Data”) for better
decision making related to planning, advertising, marketing etc.
54

DATABASE USERS – ACTORS BEHIND THE
SCENE
 System Designers and Implementors: Design and implement DBMS packages
in the form of modules and interfaces and test and debug them. The
DBMS must interface with applications, language compilers, operating
system components, etc.
 Tool Developers: Design and implement software systems called tools for
modeling and designing databases, performance monitoring,
prototyping, test data generation, user interface creation, simulation
etc. that facilitate building of applications and allow using database
effectively.
 Operators and Maintenance Personnel: They manage the actual running and
maintenance of the database system hardware and software
environment.
55

ADVANTAGES OF USING THE DATABASE
APPROACH
Controlling redundancy in data storage and in development and maintenance efforts.
 Sharing of data among multiple users.
Restricting unauthorized access to data. Only the DBA staff uses privileged
commands and facilities.
Providing persistent storage for program Objects
 E.g., Object-oriented DBMSs make program objects persistent– see Chapter 12.
Providing Storage Structures (e.g. indexes) for efficient Query Processing – see
Chapter 17.
56

ADVANTAGES OF USING THE DATABASE APPROACH (CONT.)
Providing optimization of queries for efficient processing.
Providing backup and recovery services.
Providing multiple interfaces to different classes of users.
Representing complex relationships among data.
Enforcing integrity constraints on the database.
Drawing inferences and actions from the stored data using deductive and active rules
and triggers.
57

ADDITIONAL IMPLICATIONS OF USING THE DATABASE
APPROACH
Potential for enforcing standards:
 This is very crucial for the success of database applications in large organizations.
Standards refer to data item names, display formats, screens, report structures,
meta-data (description of data), Web page layouts, etc.
Reduced application development time:
 Incremental time to add each new application is reduced.
58

ADDITIONAL IMPLICATIONS OF USING THE DATABASE
APPROACH (CONT.)
Flexibility to change data structures:
 Database structure may evolve as new requirements are defined.
Availability of current information:
 Extremely important for on-line transaction systems such as shopping, airline, hotel,
car reservations.
Economies of scale:
 Wasteful overlap of resources and personnel can be avoided by consolidating data
and applications across departments.
59

HISTORICAL DEVELOPMENT OF DATABASE
TECHNOLOGY
Early Database Applications:
 The Hierarchical and Network Models were introduced in mid 1960s
and dominated during the seventies.
 A bulk of the worldwide database processing still occurs using these
models, particularly, the hierarchical model using IBM’s IMS system.
Relational Model based Systems:
 Relational model was originally introduced in 1970, was heavily
researched and experimented within IBM Research and several
universities.
 Relational DBMS Products emerged in the early 1980s.
60

TECHNOLOGY (CONT.)
Object-oriented and emerging applications:
 Object-Oriented Database Management Systems (OODBMSs)
were introduced in late 1980s and early 1990s to cater to the
need of complex data processing in CAD and other applications.
 Their use has not taken off much.
 Many relational DBMSs have incorporated object database
concepts, leading to a new category called object-relational
DBMSs (ORDBMSs)
 Extended relational systems add further capabilities (e.g. for
multimedia data, text, XML, and other data types)
61

TECHNOLOGY (CONT.)
Data on the Web and E-commerce Applications:
 Web contains data in HTML (Hypertext markup language) with links among pages.
 This has given rise to a new set of applications and E-commerce is using new
standards like XML (eXtended Markup Language). (see Ch. 13).
 Script programming languages such as PHP and JavaScript allow generation of
dynamic Web pages that are partially generated from a database (see Ch. 11).
 Also allow database updates through Web pages
62

EXTENDING DATABASE CAPABILITIES
New functionality is being added to DBMSs in the following areas:
 Scientific Applications – Physics, Chemistry, Biology - Genetics
 Earth and Atmospheric Sciences and Astronomy
 XML (eXtensible Markup Language)
 Image Storage and Management
 Audio and Video Data Management
 Data Warehousing and Data Mining – a very major area for future
development using new technologies (see Chapters 28-29)
 Spatial Data Management and Location Based Services
 Time Series and Historical Data Management
The above gives rise to new research and development in incorporating new
data types, complex data structures, new operations and storage and
indexing schemes in database systems.
63

(CONT.)
Background since the advent of the 21st
Century:
 First decade of the 21st
century has seen tremendous growth in
user generated data and automatically collected data from
applications and search engines.
 Social Media platforms such as Facebook and Twitter are
generating millions of transactions a day and businesses are
interested to tap into this data to “understand” the users
 Cloud Storage and Backup is making unlimited amount of storage
available to users and applications
64

(CONT.)
Emergence of Big Data Technologies and NOSQL databases
 New data storage, management and analysis technology was necessary to
deal with the onslaught of data in petabytes a day (10**15 bytes or 1000
terabytes) in some applications – this started being commonly called as “Big
Data”.
 Hadoop (which originated from Yahoo) and Mapreduce Programming approach
to distributed data processing (which originated from Google) as well as the
Google file system have given rise to Big Data technologies (Chapter 25).
Further enhancements are taking place in the form of Spark based technology.
 NOSQL (Not Only SQL- where SQL is the de facto standard language for
relational DBMSs) systems have been designed for rapid search and retrieval
from documents, processing of huge graphs occurring on social networks, and
other forms of unstructured data with flexible models of transaction
processing (Chapter 24).
65

WHEN NOT TO USE A DBMS
Main inhibitors (costs) of using a DBMS:
 High initial investment and possible need for additional hardware.
 Overhead for providing generality, security, concurrency control, recovery,
and integrity functions.
When a DBMS may be unnecessary:
 If the database and applications are simple, well defined, and not
expected to change.
 If access to data by multiple users is not required.
When a DBMS may be infeasible:
 In embedded systems where a general purpose DBMS may not fit in
available storage
66

WHEN NOT TO USE A DBMS
When no DBMS may suffice:
If there are stringent real-time requirements
that may not be met because of DBMS
overhead (e.g., telephone switching systems)
 If the database system is not able to handle the complexity of data because of
modeling limitations (e.g., in complex genome and protein databases)
 If the database users need special operations not supported by the DBMS (e.g., GIS
and location based services).
67

PART 2
DATABASE SYSTEM CONCEPTS
AND ARCHITECTURE
68

LEARNİNG OBJECTİVES
List data models and their categories
Interpret the history of data models
Understand schemas, instances, and states
Evaluate the Three-Schema Architecture
Appraise data independence
Name DBMS languages and interfaces
Identify database system utilities and tools
Know the difference between centralized and client-
server architectures
Classify DBMSs
69

OUTLİNE
Data Models and Their Categories
History of Data Models
Schemas, Instances, and States
Three-Schema Architecture
Data Independence
DBMS Languages and Interfaces
Database System Utilities and Tools
Centralized and Client-Server Architectures
Classification of DBMSs
70

DATA MODELS
Data Model:
 A set of concepts to describe the structure of a database, the
operations for manipulating these structures, and certain constraints
that the database should obey.
Data Model Structure and Constraints:
 Constructs are used to define the database structure
 Constructs typically include elements (and their data types) as well as
groups of elements (e.g. entity, record, table), and relationships
among such groups
 Constraints specify some restrictions on valid data; these constraints
must be enforced at all times
71

DATA MODELS (CONTINUED)
Data Model Operations:
 These operations are used for specifying database retrievals and updates by
referring to the constructs of the data model.
 Operations on the data model may include basic model operations (e.g. generic
insert, delete, update) and user-defined operations (e.g. compute_student_gpa,
update_inventory)
72

CATEGORIES OF DATA MODELS
Conceptual (high-level, semantic) data models:
 Provide concepts that are close to the way many users perceive data.
 (Also called entity-based or object-based data models.)
Physical (low-level, internal) data models:
 Provide concepts that describe details of how data is stored in the
computer. These are usually specified in an ad-hoc manner through
DBMS design and administration manuals
Implementation (representational) data models:
 Provide concepts that fall between the above two, used by many
commercial DBMS implementations (e.g. relational data models
used in many commercial systems).
Self-Describing Data Models:
 Combine the description of data with the data values. Examples
include XML, key-value stores and some NOSQL systems.
73

SCHEMAS VERSUS INSTANCES
Database Schema:
 The description of a database.
 Includes descriptions of the database structure, data types, and the constraints on
the database.
Schema Diagram:
 An illustrative display of (most aspects of) a database schema.
Schema Construct:
 A component of the schema or an object within the schema, e.g., STUDENT,
COURSE.
74

SCHEMAS VERSUS INSTANCES
Database State:
 The actual data stored in a database at a particular moment in time. This includes
the collection of all the data in the database.
 Also called database instance (or occurrence or snapshot).
 The term instance is also applied to individual database components, e.g. record
instance, table instance, entity instance
75

DATABASE SCHEMA VS. DATABASE STATE
Database State:
 Refers to the content of a database at a moment in time.
Initial Database State:
 Refers to the database state when it is initially loaded into the system.
Valid State:
 A state that satisfies the structure and constraints of the database.
76

DATABASE SCHEMA VS. DATABASE STATE (CONT.)
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.
77

EXAMPLE OF A DATABASE SCHEMA
78

EXAMPLE OF A DATABASE STATE
79

THREE-SCHEMA ARCHITECTURE
Proposed to support DBMS characteristics of:
 Program-data independence.
 Support of multiple views of the data.
Not explicitly used in commercial DBMS products, but has been useful in explaining
database system organization
80

THREE-SCHEMA ARCHITECTURE
Defines DBMS schemas at three levels:
 Internal schema at the internal level to describe physical storage
structures and access paths (e.g indexes).
 Typically uses a physical data model.
 Conceptual schema at the conceptual level to describe the
structure and constraints for the whole database for a community
of users.
 Uses a conceptual or an implementation data model.
 External schemas at the external level to describe the various user
views.
 Usually uses the same data model as the conceptual schema.
81

THREE-SCHEMA ARCHITECTURE (CONT.)
82

THREE-SCHEMA ARCHITECTURE (CONT.)
Mappings among schema levels are needed to transform requests and data.
 Programs refer to an external schema, and are mapped by the DBMS to the internal
schema for execution.
 Data extracted from the internal DBMS level is reformatted to match the user’s
external view (e.g. formatting the results of an SQL query for display in a Web page)
83

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
84

DATA INDEPENDENCE (CONT.)
When a schema at a lower level is changed, only the mappings between this schema
and higher-level schemas need to be changed in a DBMS that fully supports data
independence.
The higher-level schemas themselves are unchanged.
 Hence, the application programs need not be changed since they refer to the
external schemas.
85

DBMS LANGUAGES
Data Definition Language (DDL)
Data Manipulation Language (DML)
 High-Level or Non-procedural Languages: These include the relational language SQL
 May be used in a standalone way or may be embedded in a programming
language
 Low Level or Procedural Languages:
 These must be embedded in a programming language
86

DBMS LANGUAGES (CONT.)
Data Definition Language (DDL):
 Used by the DBA and database designers to specify the conceptual schema of a
database.
 In many DBMSs, the DDL is also used to define internal and external schemas
(views).
 In some DBMSs, separate storage definition language (SDL) and view definition
language (VDL) are used to define internal and external schemas.
 SDL is typically realized via DBMS commands provided to the DBA and database
designers
87

DBMS LANGUAGES (CONT.)
Data Manipulation Language (DML):
 Used to specify database retrievals and updates
 DML commands (data sublanguage) can be embedded in a general-purpose
programming language (host language), such as COBOL, C,
C++, or Java.
 A library of functions can also be provided to access the DBMS from a
programming language
 Alternatively, stand-alone DML commands can be applied directly (called a query
language).
88

TYPES OF DML
High Level or Non-procedural Language:
 For example, the SQL relational language
 Are “set”-oriented and specify what data to retrieve rather than how to retrieve it.
 Also called declarative languages.
Low Level or Procedural Language:
 Retrieve data one record-at-a-time;
 Constructs such as looping are needed to retrieve multiple records, along with
positioning pointers.
89

DBMS INTERFACES
Stand-alone query language interfaces
 Example: Entering SQL queries at the DBMS interactive SQL interface (e.g.
SQL*Plus in ORACLE)
Programmer interfaces for embedding DML in programming languages
User-friendly interfaces
 Menu-based, forms-based, graphics-based, etc.
Mobile Interfaces:interfaces allowing users to perform transactions using mobile apps
90

DBMS PROGRAMMING LANGUAGE
INTERFACES
Programmer interfaces for embedding DML in a programming languages:
 Embedded Approach: e.g embedded SQL (for C, C++, etc.), SQLJ
(for Java)
 Procedure Call Approach: e.g. JDBC for Java, ODBC (Open Databse
Connectivity) for other programming languages as API’s
(application programming interfaces)
 Database Programming Language Approach: e.g. ORACLE has
PL/SQL, a programming language based on SQL; language
incorporates SQL and its data types as integral components
 Scripting Languages: PHP (client-side scripting) and Python
(server-side scripting) are used to write database programs.
91

USER-FRIENDLY DBMS INTERFACES
 Menu-based (Web-based), popular for browsing on the web
 Forms-based, designed for naïve users used to filling in entries on a form
 Graphics-based
 Point and Click, Drag and Drop, etc.
 Specifying a query on a schema diagram
 Natural language: requests in written English
 Combinations of the above:
 For example, both menus and forms used extensively in Web database interfaces
92

OTHER DBMS INTERFACES
 Natural language: free text as a query
 Speech : Input query and Output response
 Web Browser with keyword search
 Parametric interfaces, e.g., bank tellers using function keys.
 Interfaces for the DBA:
 Creating user accounts, granting authorizations
 Setting system parameters
 Changing schemas or access paths
93

DATABASE SYSTEM UTILITIES
To perform certain functions such as:
 Loading data stored in files into a database. Includes data conversion tools.
 Backing up the database periodically on tape.
 Reorganizing database file structures.
 Performance monitoring utilities.
 Report generation utilities.
 Other functions, such as sorting, user monitoring, data compression, etc.
94

OTHER TOOLS
Data dictionary / repository:
 Used to store schema descriptions and other information such as design decisions,
application program descriptions, user information, usage standards, etc.
 Active data dictionary is accessed by DBMS software and users/DBA.
 Passive data dictionary is accessed by users/DBA only.
95

OTHER TOOLS
Application Development Environments and CASE (computer-aided software
engineering) tools:
Examples:
 PowerBuilder (Sybase)
 JBuilder (Borland)
 JDeveloper 10G (Oracle)
96

TYPICAL DBMS COMPONENT MODULES
97

CENTRALIZED AND
CLIENT-SERVER DBMS ARCHITECTURES
Centralized DBMS:
 Combines everything into single system including- DBMS software, hardware,
application programs, and user interface processing software.
 User can still connect through a remote terminal – however, all processing is done
at centralized site.
98

A PHYSICAL CENTRALIZED ARCHITECTURE
99

BASIC 2-TIER CLIENT-SERVER
ARCHITECTURES
Specialized Servers with Specialized functions
 Print server
 File server
 DBMS server
 Web server
 Email server
Clients can access the specialized servers as needed
10
0

LOGICAL TWO-TIER CLIENT SERVER
ARCHITECTURE
10
1

CLIENTS
Provide appropriate interfaces through a client software module to access and utilize
the various server resources.
Clients may be diskless machines or PCs or Workstations with disks with only the
client software installed.
Connected to the servers via some form of a network.
 (LAN: local area network, wireless network, etc.)
10
2

DBMS SERVER
Provides database query and transaction services to the
clients
Relational DBMS servers are often called SQL servers,
query servers, or transaction servers
Applications running on clients utilize an Application
Program Interface (API) to access server databases
via standard interface such as:
 ODBC: Open Database Connectivity standard
 JDBC: for Java programming access
10
3

TWO TIER CLIENT-SERVER ARCHITECTURE
Client and server must install appropriate client module and server module software
for ODBC or JDBC
A client program may connect to several DBMSs, sometimes called the data sources.
In general, data sources can be files or other non-DBMS software that manages data.
See Chapter 10 for details on Database Programming
10
4

THREE TIER CLIENT-SERVER ARCHITECTURE
Common for Web applications
Intermediate Layer called Application Server or Web Server:
 Stores the web connectivity software and the business logic part of
the application used to access the corresponding data from the
database server
 Acts like a conduit for sending partially processed data between the
database server and the client.
Three-tier Architecture Can Enhance Security:
 Database server only accessible via middle tier
 Clients cannot directly access database server
 Clients contain user interfaces and Web browsers
 The client is typically a PC or a mobile device connected to the Web
10
5

THREE-TIER CLIENT-SERVER ARCHITECTURE
10
6

CLASSIFICATION OF DBMSS
Based on the data model used
 Legacy: Network, Hierarchical.
 Currently Used: Relational, Object-oriented, Object-relational
 Recent Technologies: Key-value storage systems, NOSQL systems: document based, column-based,
graph-based and key-value based. Native XML DBMSs.
Other classifications
 Single-user (typically used with personal computers)
vs. multi-user (most DBMSs).
 Centralized (uses a single computer with one database) vs. distributed (multiple computers,
multiple DBs)
10
7

VARIATIONS OF DISTRIBUTED DBMSS
(DDBMSS)
Homogeneous DDBMS
Heterogeneous DDBMS
Federated or Multidatabase Systems
 Participating Databases are loosely coupled with high degree of autonomy.
Distributed Database Systems have now come to be known as client-server based
database systems because:
 They do not support a totally distributed environment, but rather a set of database
servers supporting a set of clients.
10
8

COST CONSIDERATIONS FOR DBMSS
Cost Range: from free open-source systems to
configurations costing millions of dollars
Examples of free relational DBMSs: MySQL, PostgreSQL,
others
Commercial DBMS offer additional specialized modules,
e.g. time-series module, spatial data module,
document module, XML module
 These offer additional specialized functionality when
purchased separately
 Sometimes called cartridges (e.g., in Oracle) or blades
Different licensing options: site license, maximum
number of concurrent users (seat license), single user,
etc.
10
9

OTHER CONSIDERATIONS
Type of access paths within database system
 E.g.- inverted indexing based (ADABAS is one such system).Fully indexed databases
provide access by any keyword (used in search engines)
General Purpose vs. Special Purpose
 E.g.- Airline Reservation systems or many others-reservation systems for hotel/car
etc. Are special purpose OLTP (Online Transaction Processing Systems)
11
0

ADDITIONAL MATERIAL
HISTORY OF DATA MODELS
11
1

Network Model
Hierarchical Model
Relational Model
Object-oriented Data Models
Object-Relational Models
11
2

Network Model:
 The first network DBMS was implemented by Honeywell in 1964-65 (IDS System).
 Adopted heavily due to the support by CODASYL (Conference on Data Systems
Languages) (CODASYL - DBTG report of 1971).
 Later implemented in a large variety of systems - IDMS (Cullinet - now Computer
Associates), DMS 1100 (Unisys), IMAGE (H.P. (Hewlett-Packard)), VAX -DBMS (Digital
Equipment Corp., next COMPAQ, now H.P.).
11
3

NETWORK MODEL
Advantages:
 Network Model is able to model complex relationships and represents semantics of
add/delete on the relationships.
 Can handle most situations for modeling using record types and relationship types.
 Language is navigational; uses constructs like FIND, FIND member, FIND owner,
FIND NEXT within set, GET, etc.
 Programmers can do optimal navigation through the database.
11
4

NETWORK MODEL
Disadvantages:
 Navigational and procedural nature of processing
 Database contains a complex array of pointers that thread through a set of records.
 Little scope for automated “query optimization”
11
5

Hierarchical Data Model:
 Initially implemented in a joint effort by IBM and North American Rockwell around
1965. Resulted in the IMS family of systems.
 IBM’s IMS product had (and still has) a very large customer base worldwide
 Hierarchical model was formalized based on the IMS system
 Other systems based on this model: System 2k (SAS inc.)
11
6

HIERARCHICAL MODEL
Advantages:
 Simple to construct and operate
 Corresponds to a number of natural hierarchically organized
domains, e.g., organization (“org”) chart
 Language is simple:
 Uses constructs like GET, GET UNIQUE, GET NEXT, GET NEXT
WITHIN PARENT, etc.
Disadvantages:
 Navigational and procedural nature of processing
 Database is visualized as a linear arrangement of records
 Little scope for "query optimization"
11
7

Relational Model:
 Proposed in 1970 by E.F. Codd (IBM), first commercial
system in 1981-82.
 Now in several commercial products (e.g. DB2, ORACLE, MS
SQL Server, SYBASE, INFORMIX).
 Several free open source implementations, e.g. MySQL,
PostgreSQL
 Currently most dominant for developing database
applications.
 SQL relational standards: SQL-89 (SQL1), SQL-92 (SQL2),
SQL-99, SQL3, …
 Chapters 5 through 11 describe this model in detail
11
8

Object-oriented Data Models:
 Several models have been proposed for implementing in a
database system.
 One set comprises models of persistent O-O Programming
Languages such as C++ (e.g., in OBJECTSTORE or VERSANT),
and Smalltalk (e.g., in GEMSTONE).
 Additionally, systems like O2, ORION (at MCC - then ITASCA),
IRIS (at H.P.- used in Open OODB).
 Object Database Standard: ODMG-93, ODMG-version 2.0,
ODMG-version 3.0.
 Chapter 12 describes this model.
11
9

Object-Relational Models:
 The trend to mix object models with relational was started with Informix Universal
Server.
 Relational systems incorporated concepts from object databases leading to object-
relational.
 Exemplified in the versions of Oracle, DB2, and SQL Server and other DBMSs.
 Current trend by Relational DBMS vendors is to extend relational DBMSs with
capability to process XML, Text and other data types.
 The term “Object-relational” is receding in the marketplace.
12
0

DataBaseManagementSystems OVERVIEW and introduction

More Related Content

Similar to DataBaseManagementSystems OVERVIEW and introduction (20)

Recently uploaded (20)

DataBaseManagementSystems OVERVIEW and introduction