Concepts of Distributed databases

A Distributed database is defined as a logically related collection of data that is shared which is physically distributed over a computer network on different sites. Distributed DBMS : The Distributed DBMS is defined as, the software that allows for the management of the distributed database and make the distributed data available for the users. A distributed DBMS consist of a single logical database that is divided into a number of pieces called the fragments. In DDBMS, Each site is capable of independently processing the users request. Users can access the DDBMS via applications classified:

1. Local Applications - Those applications that doesn't require data from the other sites are classified under the category of Local applications.
2. Global Applications - Those applications that require data from the other sites are classified under the category of Global applications.

Characteristics of Distributed DDBMS : A DDBMS has the following characteristics-

1. A collection of logically related shared data.
2. The data is split into a number of fragments.
3. Fragments may be duplicate.
4. Fragments are allocated to sites.
5. The data at each site is under the control of DBMS and managed by DBMS.

Distributed Processing : The Distributed processing is centralized database that can be accessed over a computer network by different sites. The data is centralized even though other users may be accessing the data from the other sites, we do not consider this to be DDBMS, simply distributed processing. Parallel DBMS : A parallel DBMS is a DBMS that run across multiple processor and is designed to execute operations in parallel, whenever possible. The parallel DBMS link a number of smaller machines to achieve same throughput as expected from a single large machine. There are three main architectures for Parallel DBMS-

1. Shared Memory - Shared memory is a highly coupled architecture in which a number of processors within a single system who share system memory. It is also known as symmetric multiprocessing (SMP). This approach is more popular on platforms like personal workstations that support a few microprocessor in parallel.
2. Shared Disk - Shared disk is a loosely coupled architecture used for application that are centralized and require a high availability and performance.Each processor is able to access all disks directly, but each has it's own private memory.It is also called Clusters.
3. Shared Nothing - Shared nothing is a multiple processor architecture in which every processor is a part of a complete system, which has its own memory and disk storage( has it's own resources). It is also called Massively Parallel Processing (MPP).