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CAP theorem

The CAP theorem, proposed by computer scientist Eric Brewer, states that in a distributed data system, you can only fully achieve two out of three key properties: Consistency (all nodes see the same data at the same time), Availability (every request receives a response, whether successful or not), and Partition Tolerance (the system continues to operate even if some nodes can't communicate). In practice, this means that during network issues, a system must prioritize either consistent data or the ability to respond to requests, but cannot guarantee both simultaneously.

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    The CAP Theorem states that in a distributed data system, you can only ensure two out of the following three guarantees at the same time: Consistency (all nodes see the same data at the same time), Availability (the system is always operational and responsive), and Partition Tolerance (the system continues to function despite network failures). In practice, this means that if a network issue occurs, a system must choose between maintaining consistent data or remaining available to users. Understanding these trade-offs helps in designing data systems that best meet user needs.