Transcript 2440: 180 Database Concepts - gozips.uakron.edu

The University of Akron
Dept of Business Technology
Computer Information Systems
2440: 180
Database Concepts
Instructor: Enoch E. Damson
Database Management Approaches
Distributed Databases
• Computers at various sites
• Distributed database is single logical database
physically divided among networked computers
• DDBMS supports and manipulates distributed
databases
Database Management
Approaches
• Connected with communications network
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Characteristics of
Distributed DBMSs
• Homogeneous
• Heterogeneous
• At least two sites with different DBMSs
Database Management
Approaches
• Same local DBMS at each site
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Characteristics of
Distributed DBMSs…
• Location transparency
• Replication transparency
• User unaware of behind the scenes replication of
the data
• Fragmentation transparency
Database Management
Approaches
• User feels as though entire database is at their site
• Logical object divided among various locations
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Advantages of
Distributed Databases
• Local control of data
• Increased database capability
• Added system availability
• Though parts of a database may not be accessible,
transactions can still occur, increasing overall
availability of the database
Database Management
Approaches
• Possible legal reasons for local control over data used
in a particular geographic region
• Added efficiency
• Smaller tables are faster to query
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Disadvantages of
Distributed Databases
• Problems updating replicated data
• More complex treatment of concurrent update
• More complex recovery measures
• More difficult management of the data dictionary
Database Management
Approaches
• More complex query processing
• More complex database design
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Rules for Distributed Databases
• Local autonomy
• Continuous operation
• Location transparency
Database Management
Approaches
• No reliance on a central site
• Fragmentation transparency
• Replication transparency
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Rules for Distributed Databases…
• Distributed query processing
• Hardware independence
• Operating system independence
Database Management
Approaches
• Distributed transaction management
• Network independence
• DBMS independence
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Client-Server Systems
• Tiered approach to developing systems
• Typical systems will implement two tiers
• Server
• Server manages all access to data
• Client consults server for most processing
Database Management
Approaches
• Client
• Some systems almost totally abstract the client from
any processing by introducing a middle tier to handle
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all logic or processing
Advantages of
Client/Server Systems
• Improved processing distribution
• Thinner clients
• Greater processing transparency
Database Management
Approaches
• Lower network traffic
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Advantages of
Client/Server Systems…
• Improved security
• Decreased costs
Database Management
Approaches
• Increased network, hardware, and software
transparency
• Increased scalability
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Triggers and Stored Procedures
• Triggers
• Created by programmers
• Use special SQL statements
• Stored Procedures
• Collection of SQL statements compiled and
optimized by DBMS
• Improves performance
Database Management
Approaches
• Actions that occurs automatically in response to a
particular database operation
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Data Warehouses
• Used for analysis of existing data
Database Management
Approaches
• Subject-oriented, integrated, time-variant,
nonvolatile collection of data in support of
management’s decision-making process
• Resolves performance issues suffered by operational
RDBMSs and OLTPs
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On-Line Analytical Processing
• Optimized to work with data warehouses
• Allows users to perceive data as a
multidimensional data cube
• Slice and dice
• Drill down
Database Management
Approaches
• Used to answer questions
• Roll Up
• Data mining
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Rules for OLAP Systems
• Multidimensional conceptual view
• Accessibility
• Consistent reporting performance
Database Management
Approaches
• Transparency
• Client/server architecture
• Generic dimensionality
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Rules for OLAP Systems
• Dynamic sparse matrix handling
• Unrestricted, cross-dimensional operations
• Intuitive data manipulation
Database Management
Approaches
• Multiuser support
• Flexible reporting
• Unlimited dimensions and aggregation levels
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Object-Oriented DBMS (OODBMS)
• Store graphics, drawings, video, sound, and other
complex objects called binary large objects (BLOBs)
• General concepts
• Objects and classes
Database Management
Approaches
• System in which data and methods operating on
that data are encapsulated into objects
• Methods and messages
• Inheritance
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Unified Modeling Language (UML)
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Class
Use Case
State
Sequence
Activity
Collaboration
Component
Database Management
Approaches
• Models various aspects of software development
for OO systems
• Includes several types of diagrams
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Database Management
Approaches
Class Diagram with Constraints
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Database Management
Approaches
Class Diagram with a
Generalization and a
Constraint
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Rules for OODBMSs
• Complex objects
• Encapsulation
• Information hiding
• Types of classes
Database Management
Approaches
• Object identity
• Inheritance
• Late binding
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Rules for OODBMSs…
• Computational completeness
• Persistence
• Performance
• Concurrent update support
Database Management
Approaches
• Extensibility
• Recovery support
• Query facility
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Web Access to Databases
• Electronic Commerce
• Business to Business
• Business to Consumer
• Internet facilitating better access to data
• Extensible Markup Language (XML)
Database Management
Approaches
• Conducting business on the Internet
• Key technology to data interchange between systems
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History of Database Management
• Early systems
• GUAM, DL/I, IMS, IDS, IDMS
• DB2, Oracle, Sybase, Paradox, dBASE, Access,
MySQL, SQL Server
• OODBMSs
Database Management
Approaches
• Relational products
• Gemstone, Objectivity/DB, Versant
• ORDBMSs
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Hierarchical and Network Databases
• Structure is how users perceive data to be structured
• Operations are facilities given to users to interact
with data
• Users perceive a network model database as a
collection of record types and relationships
• Users perceive a hierarchical model as a collection
of hierarchies or trees
Database Management
Approaches
• Data models have two components, structure and
operations
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