In parallel database system data processing performance is improved by using multiple resources in parallel. In this CPU, disks are used parallel to enhance the processing performance.
Operations like data loading and query processing are performed parallel. Centralized and client server database systems are not powerful enough to handle applications that 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, which are given below −
Let us discuss shared nothing architecture.
Shared nothing architecture − In this each node has its own mass storage as well as main memory. The processor at one node may communicate with another processor at another node by a high speed interconnection network. The node functions as the server for the data on the disk or disks that the node owns as each processor has its own copy of OS, DBMS and data.
Examples − Teradata, Gamma, Bubba.
Given below is the diagram of the shared nothing architecture −
The advantages of the shared nothing architecture are as follows −
The interconnection network for shared-nothing models is usually designed to be scalable so that their transmission capacity increases as more nodes are added.Thus these architectures are more scalable and easily support a large number of processors.
It overcomes the disadvantages requiring all I/O to go through a single intercommunication network.
It provides linear speed-up and linear scale-up that is time taken for operations decreases in proportion to the increase in the number of CPU’s and disks; scale-up means the performance is sustained if the number of CPU’s and disks are increased in proportion to the amount of data.
The disadvantages of the shared nothing architecture are as follows −
CPU to CPU communication is very slow.
The cost of communication and no-local disk access are higher than shared memory or shared disk architecture because sending data involves software interaction at both sides.
Shared nothing architecture is difficult to load balance.