Summer 2014 CIS 40

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Distributed
Database
Management
System
Jeffrey Chin
CIS 40
Prof. Villegas
Summer 2014

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During 1970s, corporations implemented centralized
database management systems to meet their structured
information needs. such information, generated by
procedural programming languages. The centralized
approach fell short when quickly moving events required
faster response times and equally quick access to
information.
History and Why We Need DDBMS ?

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Governs the storage and processing of logically related
data over interconnected computer systems in which both
data and processing functions are distributed among
several sites.
What is Distributed database
management systems (DDBMS) ?

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Site 5
Site 1
Site 2
Site 3Site 4
Communication
Network
Distributed DBMS Environment

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 All sites use same DBMS product.
 Much easier to design and manage.
 Approach provides incremental growth and allows
increased performance.
Homogeneous DDBMS

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 Sites may run different DBMS products, with possibly
different underlying data models.
 Occurs when sites have implemented their own databases
and integration is considered later.
 Translations required to allow for:
 Different hardware.
 Different DBMS products.
 Different hardware and different DBMS products.
Heterogeneous DDBMS

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Must include (at least) the following components:
 Computer workstations
 Network hardware and software
 Allows all sites to interact and exchange data
 Communications media
 Carry the data from one workstation to another
 Transaction processor (application processor or
transaction manager)
 Software component found in each computer that
receives and processes the application’s requests
data
DDBMS Components

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 Data processor or data manager
 Software component residing on each computer
that stores and retrieves data located at the site
 May even be a centralized DBMS
 Communications between the TPs and DPs is
made possible through a set of protocols used by
the DDBMS
DDBMS Components (Continued)

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 Data fragmentation:
 How to partition the database into fragments
 Data replication:
 Which fragments to replicate
 Data allocation:
 Where to locate those fragments and replicas
Distributed Database Design

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 Breaks single object into two or more segments or fragments
 Each fragment can be stored at any site over a computer network
 Information about data fragmentation is stored in the distributed data
catalog (DDC), from which it is accessed by the TP to process user
requests
Data Fragmentation

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 Horizontal fragmentation:
 Division of a relation into subsets (fragments) of tuples (rows)
 Vertical fragmentation:
 Division of a relation into attribute (column) subsets
 Mixed fragmentation:
 Combination of horizontal and vertical strategies
Data Fragmentation Strategies

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 Storage of data copies at multiple sites served by a computer network
 Fragment copies can be stored at several sites to serve specific
information requirements
 Can enhance data availability and response time
 Can help to reduce communication and total query costs
 Imposes additional processing overhead
 Which copy do you read when submitting a query
 All copies must be updated when a write occurs
Data Replication

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 Deciding where to locate data
 Allocation strategies:
 Centralized data allocation
 Entire database is stored at one site
 Partitioned data allocation
 Database is divided into several disjointed parts (fragments) and
stored at several sites
 Replicated data allocation
 Copies of one or more database fragments are stored at several
sites
 Data distribution over a computer network is achieved through data
partition, data replication, or a combination of both
Data Allocation

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 Manufacturing - especially multi-plant
manufacturing
 Military command and control
 Corporate MIS
 Airlines
 Hotel chains
 Any organization which has a decentralized
organization structure
Applications of DDBMS

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 Data are located near “greatest demand” site
 Faster data access
 Faster data processing
 Growth facilitation
 Improved communications
 Reduced operating costs
 User-friendly interface
 Less danger of a single-point failure
 Processor independence
DDBMS Advantages

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Complexity of management and control
Security
Lack of standards
Increased storage requirements
Greater difficulty in managing the data environment
Increased training cost
DDBMS Disadvantages