Distributed database in dbms

A distributed database in dbms storage devices are not all sticked to a common CPU. It may be stored in multiple pc’s located in the same physical location, or may be dispersed over a network of interconnected pc’s.

Distributed Database Management System

A centralized DDBMS (distributed database management system ) manages the database as if it were all stored on the same computer. The distributed database management system synchronizes all the data in a time period and, in cases where multiple users must access the same data, provided that updates and deletes performed on the file at one location will be automatically reflected in the data stored somewhere else.

The users and admin of a distributed system, should be with proper implementation, communicate with the system as if the system was centralized. This transparency allows for the functionality desired in such a structured system without special programming requirements, allowing for any number of local and/or remote tables to be accessed at a given time across all the network.

The various types of transparency sought after in a DDBMS are data distribution transparency, heterogeneity transparency, transaction transparency, and performance transparency. Data distribution transparency requires that the user of the database shouldn’t have to know how the data is separated (fragmentation transparency), know where the data they access is normally placed (location transparency), or be aware of whether multiple copies of the data already exist (replication transparency). Heterogeneity transparency requires that the user should not be aware of the fact that they are using a different DBMS if they access data from a remote site. The user should be able to use the same language that they would normally use at their regular access point and the DDBMS should handle query language translation if needed. Transaction transparency requires that the DDBMS guarantee that concurrent transactions do not interfere with each other (concurrency transparency) and that it must also handle database recovery (recovery transparency). Performance transparency mandates that the DDBMS should have a comparable level of performance to a centralized DBMS. Query optimizers can be used to speed up response time.

4 Types of DDB Design

Non-Partitioned, Non-Replicated

Partitioned, Non-Replicated

Non-Partitioned, Replicated

Partitioned, Replicated

DDBMS Advantages and Disadvantages

Distributed database management systems deliver several advantages over traditional systems. That being said, they are subject to some problems.

Advantages of DDBMS’s
– Reflects organizational structure

– Improved share ability, availability, reliability, performance

– Data are located nearest the greatest demand site and are dispersed to match business requirements.

– Faster Data Access because users only work with a locally stored subset of the data.

– Faster data processing because the data is processed at several different sites.

-Growth Facilitation

-Improved communications because local sites are smaller & closer to customers.

– Reduced operating costs

– User Friendly interface equipped with an easy-to-use Graphic User Interface.

– Less instances of single-point failure because data and workload are distributed among other workstations.

– The end user is able to access any available copy of data – Processor independence

Disadvantages of DDBMS’s

– Increased Cost

-Integrity control more difficult,

-Lack of standards,

-Database design more complex.

– Complexity of management and control. Applications must recognize data location and they must be able to stitch together data from various sites.

– Technologically difficult: they are,

Data integrity, transaction management, concurrency control, security, backup, recovery, query optimization, access path selection are all issues that must be addressed.

– Security lapses have increased instances when data are in multiple locations.

– Lack of standards due to the absence of communication protocols can make the processing and distribution of data difficult.

– more disk space.

 

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