Distributed Database Architecture

Data independence:
Logical data independence: 
User application should not be affected by the logical data independence. 
Physical independence: 
Hiding the details of storage structure. 
only the centralized DBMS form is important. 

Naming Transparency:

location transparency:
An operation performed on the data is independent of both location and system where it is executed. 
Naming transparency :
Unique name is assigned to each identifiers. 

Transparency:

Higher level semantics is separated from the lower level semantics. 
Hiding implementation from the users. 
Forms: 
Network transparency 
data transparency
fragmentation transparency 
replication transparency 

Transparency can be provided at different level of the systems. 

Replication transparency: 
Data is replicated for reliability and performance consideration. 
Fragment transparency: 
DB relation are divided into smaller fragments for performance and availability reasons. 

The origin of transparency:

Access layer : Transparency feature are built into user language that is translated into requested operations 
DBMS: act as an integrated OS and DBMS,make necessary translation between OS and user interface 
OS: transparent access is provided to resources. 

DBMS architecture:

Based on components: the components and their interrelations are defined.
Based on functions: The functions that the system will perform are defined. 
Based on data: Different type of data and functional unit that will use data are defined/ 

Usually there is an interplay among them. 

Architecture: 
Architecture of a system defines the structure.
Model:
In the foreign part of the structure there is the reference model. 
it is idealized view,
it is different from real world example but gives reasonable framework.
Goal: 
present the issues that need to be addressed.
present a framework with in which the design and implementation can be discussed. 

ANSI model:
A model from the 70's but still provide the interest and is the basis of distributed database systems.
Bases on data organization:

External view:   highest level of user view of the portion and relationship among data.
conceptual view: Abstract definition of the database the real world view. 
internal view:  lowest level physical definition storage issue.






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