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Databases and Database Management Systems

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Used by the DBA and database designers to specify the conceptual schema of a database. ... model used: Traditional: Relational, Network, Hierarchical. Emerging: ... – PowerPoint PPT presentation

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Title: Databases and Database Management Systems


1
Databases and Database Management Systems
  • Based on Chapters 1-2 in Fundamentals of
    Database Systems
  • by Elmasri and Navathe, Ed. 4

2
NOTES
  • 1 Basic Definitions
  • 2 Example of a Database
  • 3 Main Characteristics of Database Technology
  • 4 Additional Benefits of Database Technology
  • 5 When Not to Use a DBMS
  • 6 Data Models6A. History of data Models
  • 7 Schemas versus Instances
  • 8 Three-Schema Architecture
  • 9 Data Independence
  • 10 DBMS Languages
  • 11 DBMS Interfaces
  • 12 DBMS Component Modules
    13 Database System Utilities
  • 14 Classification of DBMSs

3
Types of Databases and Database Applications
  • Numeric and Textual Databases
  • Multimedia Databases
  • Geographic Information Systems (GIS)
  • Data Warehouses
  • Real-time and Active Databases
  • A number of these databases and applications are
    described later in the book (see Chapters
    24,28,29)

4
1.Basic Definitions
  • Database
  • A collection of related data.
  • Data
  • Known facts that can be recorded and have an
    implicit meaning.

5
Basic Definitions
  • 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.

6
Basic Definitions
  • Database Management System (DBMS)
  • A software package/ system to facilitate the
    creation and maintenance of a computerized
    database.

7
Basic Definitions
  • Database System
  • The DBMS software together with the data itself.
  • Sometimes, the applications are also included.
  • Database System
  • Data DBMS (Program)

8
A simplified database system environment.
9
Typical DBMS Functionality (1/2)
  • Define a database
  • in terms of data types, structures and
    constraints
  • Construct or Load the Database on a secondary
    storage medium
  • Manipulating the database
  • querying, generating reports, insertions,
    deletions and modifications to its content
  • Concurrent Processing and Sharing by a set of
    users and programs yet, keeping all data valid
    and consistent

10
Typical DBMS Functionality (2/2)
  • Other features
  • Protection or Security measures to prevent
    unauthorized access
  • Active processing to take internal actions on
    data
  • Presentation and Visualization of data

11
2. Example of a Database(with a Conceptual Data
Model)  
  • Mini-world for the example
  • Part of a UNIVERSITY environment.
  • Entities
  • Relationships

12
2. Example of a Database(with a Conceptual Data
Model)
  • Some mini-world entities
  • STUDENTs
  • COURSEs
  • SECTIONs (of COURSEs)
  • (academic) DEPARTMENTs
  • INSTRUCTORs

13
2. Example of a Database(with a Conceptual Data
Model)
  • 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

14
NOTE
  • The above could be expressed in the
    ENTITY-RELATIONSHIP data model.

15
3. Main Characteristics of Database Technology
  • Self-contained nature of a database system
  • Insulation(??) between programs and data
  • Data Abstraction
  • Support of multiple views of the data
  • Sharing of data and multiuser transaction
    processing

16
Self-contained nature of a database system
  • A DBMS catalog stores the description of the
    database.
  • The description is called meta-data.
  • This allows the DBMS software to work with
    different databases.

17
Insulation between programs and data
  • Called program-data independence.
  • Allows changing data storage structures and
    operations without having to change the DBMS
    access programs.

18
Data Abstraction
  • A data model is used to hide storage details and
    present the users with a conceptual view of the
    database.

19
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.

20
The STUDENT TRANSCRIPT view.
21
University database
22
Internal storage format for a STUDENT record
23
Sharing of data and multiuser transaction
processing
  • allowing a set of concurrent users to retrieve
    and to update the database.
  • Concurrency control within the DBMS guarantees
    that each transaction is correctly executed or
    completely aborted.
  • OLTP (Online Transaction Processing) is a major
    part of database applications.

24
4. Additional Benefits of Database Technology
  • Controlling redundancy in data storage and in
    development and maintenance efforts.
  • Sharing of data among multiple users.
  • Restricting unauthorized access to data.
  • Providing multiple interfaces to different
    classes of users.
  • Representing complex relationships among data.
  • Enforcing integrity constraints on the database.
  • Providing backup and recovery services.
  • Potential for enforcing standards.
  • Flexibility to change data structures.
  • Reduced application development time.
  • Availability of up-to-date information.
  • Economies of scale.

25
Redundant storage of StudentName and CourseNumber
in GRADE_REPORT.
(a) Consistent data.
(b) Inconsistent record.
26
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.

27
Historical Development of Database Technology
  • Relational Model based Systems
  • The model that was originally introduced in 1970
    was heavily researched and experimented with in
    IBM and the universities.
  • Relational DBMS Products emerged in the 1980s.

28
Historical Development of Database Technology
  • Object-oriented applications
  • 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.

29
Historical Development of Database Technology
  • 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).

30
Extending Database capabilities
  • New functionality is being added to DBMSs in the
    following areas
  • Scientific Applications
  • Image Storage and Management
  • Audio and Video data management
  • Data Mining
  • Spatial data management
  • Time Series and Historical Data Management

31
5 When not to use a DBMS
  • Main inhibitors (costs) of using a DBMS
  • When a DBMS may be unnecessary
  • When no DBMS may suffice

32
Main inhibitors (costs) of using a DBMS
  • High initial investment and possible need for
    additional hardware.
  • Overhead for providing generality, security,
    recovery, integrity, and concurrency control.

33
When a DBMS may be unnecessary
  • If the database and applications are simple, well
    defined, and not expected to change.
  • If there are stringent real-time requirements
    that may not be met because of DBMS overhead.
  • If access to data by multiple users is not
    required.

34
When no DBMS may suffice
  • If the database system is not able to handle the
    complexity of data because of modeling
    limitations
  • If the database users need special operations not
    supported by the DBMS.

35
6. Data Models
  • Data Model
  • A set of concepts to describe the structure of a
    database, and certain constraints that the
    database should obey.

36
6. Data Models
  • Data Model Operations
  • Operations for specifying database retrievals and
    updates by referring to the concepts of the data
    model.
  • Operations on the data model may include basic
    operations and user-defined operations

37
Categories of data models
  • Conceptual data models
  • (high-level, semantic)
  • Physical data models
  • (low-level, internal)
  • Logical (representational, Implementation) data
    models
  • (record-oriented)

38
Conceptual data models
  • Provide concepts that are close to the way many
    users perceive data.
  • Also called entity-based or object-based data
    models.

39
Physical data models
  • Provide concepts that describe details of how
    data is stored in the computer.
  • storage structure
  • Access path

40
Implementation data models
  • Also called logical data model
  • Provide concepts that fall between the above two,
    balancing user views with some computer storage
    details.

41
6A. HISTORY OF DATA MODELS
  • Relational Model
  • Network Model
  • Hierarchical Data Model
  • Object-oriented Data Model(s
  • Object-Relational Models

42
Relational Model
  • proposed in 1970 by E.F. Codd (IBM), first
    commercial system in 1981-82.
  • Now in several commercial products
  • DB2,
  • ORACLE,
  • SQL Server,
  • SYBASE,
  • INFORMIX.

43
Object-Relational Models
  • Most Recent Trend.
  • Started with Informix Universal Server.
  • Exemplified in the latest versions of Oracle-10g,
    DB2, and SQL Server etc. systems.

44
7. Schemas versus Instances
  • Database Schema
  • The description of a database.
  • Includes
  • descriptions of the database structure and
  • the constraints that should hold on the database.
  • Schema Diagram
  • A diagrammatic display of (some aspects of) a
    database schema.

45
Schema diagram for University database
46
7. Schemas versus Instances
  • Database Instance
  • The actual data stored in a database at a
    particular moment in time .
  • Also called database state (or occurrence).

47
7. Schemas versus Instances
  • Database State
  • Refers to the content of a database at a moment
    in time.
  • Initial Database State
  • Refers to the database when it is loaded
  • Valid State
  • A state that satisfies the structure and
    constraints of the database.

48
7. Schemas versus Instances
  • Distinction
  • The database schema changes very infrequently.
  • The database state changes every time the
    database is updated.
  • Schema is also called intension, whereas state is
    called extension.

49
8. Three-Schema Architecture
  • Proposed to support DBMS characteristics of
  • Program-data independence.
  • Support of multiple views of the data.

50
8. Three-Schema Architecture
  • Defines DBMS schemas at three levels
  • Internal schema
  • Conceptual schema
  • External schemas

51
The three-schema architecture.
52
Internal schema
  • Internal schema at the internal level to describe
    data storage structures and access paths.
  • Typically uses a physical data model.

53
Conceptual schema
  • Conceptual schema at the conceptual level to
    describe the structure and constraints for the
    whole database.
  • Uses a conceptual or an implementation data
    model.

54
External schemas
  • External schemas at the external level to
    describe the various user views.
  • Usually uses the same data model as the
    conceptual level.

55
Three-Schema Architecture
  • Mappings among schema levels are also needed.
  • Programs refer to an external schema, and are
    mapped by the DBMS to the internal schema for
    execution.

56
9 Data Independence
  • Logical Data Independence
  • The capacity to change the conceptual schema
    without having to change the external schemas and
    their application programs.
  • Physical Data Independence
  • The capacity to change the internal schema
    without having to change the conceptual schema.

57
Data Independence
  • 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 the refer to the external schemas.

58
10. DBMS Languages
  • Data Definition Language (DDL)
  • Data Manipulation Language (DML)
  • Data Control Language (DCL)

59
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.

60
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 C, COBOL, PL/1 or PASCAL.
  • Alternatively, stand-alone DML commands can be
    applied directly (query language).

61
DBMS Languages
  • High Level or Non-procedural Languages
  • e.g., SQL, are set-oriented and specify what
    data to retrieve than how to retrieve. Also
    called declarative languages.
  • Low Level or Procedural Languages
  • record-at-a-time they specify how to retrieve
    data and include constructs such as looping.

62
11. DBMS Interfaces
  • Stand-alone query language interfaces.
  • Programmer interfaces for embedding DML in
    programming languages
  • Pre-compiler Approach
  • Procedure (Subroutine) Call Approach
  • User-friendly interfaces
  • Web Browser as an interface
  • Parametric interfaces (e.g., bank tellers) using
    function keys.

63
DBMS Interfaces
  • Interfaces for the DBA
  • Creating accounts, granting authorizations
  • Setting system parameters
  • Changing schemas or access path

64
Component modules of a DBMS and their
interactions.
65
13. Database System Utilities
  • To perform certain functions such as
  • Loading data stored in files into a database.
  • Backing up the database periodically on tape.
  • Reorganizing database file structures.
  • Report generation utilities.
  • Performance monitoring utilities.
  • Other functions, such as sorting , user
    monitoring , data compression , etc.

66
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.

67
14. Classification of DBMSs
  • Based on data model
  • Other classifications

68
Based on the data model used
  • Traditional
  • Relational,
  • Network,
  • Hierarchical.
  • Emerging
  • Object-oriented,
  • Object-relational.

69
Other classifications
  • Single-user (typically used with micro-
    computers) vs. multi-user (most DBMSs).
  • Centralized (uses a single computer with one
    database) vs. distributed (uses multiple
    computers, multiple databases)
  • 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.

70
Example of a Database(with a Logical Data Model)
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