The common motivations of NoSQL design are:
• Easier deployment
• Large scale data
• Meeting the scalability and failover
• Can be used as a Caching layer for storing the transaction data
Key features of NoSQL are:
• ‘‘Horizontal Scaling/Scaling Out’’ for ‘‘simple operations’’ by adding more machines to a pool of resources, whereas, ‘‘Vertical Scaling/Scaling Up’’ means adding more CPU, RAM, etc. to existing machines
Scaling Up by adding new expensive big servers is difficult because of
• Hardware limitations
• Involves lots of complex Join Operation
• Requires higher level of skills
• Not reliable in some cases
• Replicate/distribute data over many servers
The RDBMS can ‘‘Scale Up’’, but not ‘‘Scale Out’’, hence suitable for strong Consistency and Availability. In most of NoSQL data is partitioned and replicated across multiple nodes. Inherently, most of them use either Google’s MapReduce or Hadoop Distributed File System or Hadoop MapReduce for data aggregation
The common motivations of NoSQL design are:• Easier deployment• Large scale data• Meeting the scalability and failover• Can be used as a Caching layer for storing the transaction dataKey features of NoSQL are:• ‘‘Horizontal Scaling/Scaling Out’’ for ‘‘simple operations’’ by adding more machines to a pool of resources, whereas, ‘‘Vertical Scaling/Scaling Up’’ means adding more CPU, RAM, etc. to existing machinesScaling Up by adding new expensive big servers is difficult because of• Hardware limitations• Involves lots of complex Join Operation• Requires higher level of skills• Not reliable in some cases• Replicate/distribute data over many serversThe RDBMS can ‘‘Scale Up’’, but not ‘‘Scale Out’’, hence suitable for strong Consistency and Availability. In most of NoSQL data is partitioned and replicated across multiple nodes. Inherently, most of them use either Google’s MapReduce or Hadoop Distributed File System or Hadoop MapReduce for data aggregation
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