What is CAP theorem in computer science?
In theoretical computer science, 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:

Consistency
Every read receives the most recent write or an error.
Availability
Every request receives a (non-error) response, without the guarantee that it contains the most recent write.
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.

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.

Eric Brewer argues that the often-used "two out of three" concept can be somewhat misleading because system designers need only to sacrifice consistency or availability in the presence of partitions, but that in many systems partitions are rare.
The CAP theorem, also named Brewer's theorem, states that distributed data stores can provide only two of three guarantees: consistency, availability, and partition tolerance. When a network partition fails, it must be decided whether to cancel the operation or proceed with the operation. Eric Brewer argues that the "two out of three" concept can be misleading.
Instruction: What is CAP theorem in computer science?
Context: In theoretical computer science, 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:

Consistency
Every read receives the most recent write or an error.
Availability
Every request receives a (non-error) response, without the guarantee that it contains the most recent write.
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.

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.

Eric Brewer argues that the often-used "two out of three" concept can be somewhat misleading because system designers need only to sacrifice consistency or availability in the presence of partitions, but that in many systems partitions are rare.
Response: The CAP theorem, also named Brewer's theorem, states that distributed data stores can provide only two of three guarantees: consistency, availability, and partition tolerance. When a network partition fails, it must be decided whether to cancel the operation or proceed with the operation. Eric Brewer argues that the "two out of three" concept can be misleading.