CAP theorem
Need to sacrifice consistency or availability in the presence of network partitions / From Wikipedia, the free encyclopedia
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In database theory, the CAP theorem, also named Brewer's theorem after computer scientist Eric Brewer, states that any distributed data store can provide only two of the following three guarantees:[1][2][3]
- Consistency
- Every read receives the most recent write or an error.
- Availability
- Every request received by a non-failing node in the system must result in a response. This is the definition of availability in CAP theorem as defined by Gilbert and Lynch.[1] Note that availability as defined in CAP theorem is different from high availability in software architecture.[4]
- Partition tolerance
- The system continues to operate despite an arbitrary number of messages being dropped (or delayed) by the network between nodes.
When a network partition failure happens, it must be decided whether to do one of the following:
- cancel the operation and thus decrease the availability but ensure consistency
- proceed with the operation and thus provide availability but risk inconsistency. Note this doesn't necessarily mean that system is highly available to its users. [5]
Thus, if there is a network partition, one has to choose between consistency or availability. Note that consistency as defined in the CAP theorem is quite different from the consistency guaranteed in ACID database transactions.[6]