In parallel database system data processing performance is improved by using multiple resources in parallel. In this CPU, the disk is used parallel to enhance the processing performance.
Operations like data loading and query processing are performed parallel. The centralized and client server database systems are not powerful enough to handle applications which need fast processing.
Parallel database systems have great advantages for online transaction processing and decision support applications. Parallel processing divides a large task into multiple tasks and each task is performed concurrently on several nodes. This gives a larger task to complete more quickly.
There are several architectural models for parallel machines. The most important one are as follows −
Shared-memory multiple CPU − Here, the computer has several simultaneously active CPUs that are attached to an interconnection network and share a single main memory and a common array of disk storage.
Shared disk architecture − Here, each node has its own main memory but all nodes share mass storage. In practice, each node also has multiple processors.
Shared nothing architecture − Here, each node has its own mass storage as well as main memory.
It is a collection of multiple interconnected databases that are spread physically across various locations that communicate via a computer network.
Distributed Database gives us the following −