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 about Hierarchical architecture.
Hierarchical Architecture − Hierarchical architecture combines the characteristics of shared memory, shared disk and shared nothing architecture.
The top level is shared nothing architecture.
Each node of the system could actually be a shared memory system with a few processors.
Alternatively, each node could be a shared disk system and each of the systems sharing a set of disk systems could be a shared memory system.
Thus, a system could be built as a hierarchy, with shared memory architecture with a few processors at the base, and shared nothing at the top, with possibly shared disk architecture in the middle.
Given below is the diagram of hierarchical architecture −
This architecture is also called cluster-based architecture.
P is the Processor.
M is the Main Memory.
It provides all the advantages of shared memory, shared disk and shared nothing architecture such as flexibility and better performance of shared memory architecture, higher data availability of shared disk architecture and high extensibility of shared nothing architecture.
The only disadvantage is its complexity.