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Explain parallel and distributed database management system
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.
Architectural Models
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.
Distributed Database
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 −
- Modular Development − The term modular development includes that when we want to expand the using system on different locations then we just need to add nodes to the current network and these nodes do not interrupt the current network functionalities.
- Increases Reliability − The term increases reliability refers to, if one node on a network fails then its work can be distributed between other nodes on the network, failing of one node does not stop the system.
- Improves Performance − We all know that a small database is easy to handle compared to a large database, so in a distributed database a large database is distributed into a small database across various locations which are easy to handle with better performance.
- Increase Availability − The failure of one node will not affect data availability because data can be obtained from various other nodes on the network.
- Faster Response − Data retrieval becomes more efficient as data is available locally.
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