CAP Theorem

https://github.com/ByteByteGoHq/system-design-101?tab=readme-ov-file#cap-theorem

The CAP theorem, also known as Brewer’s theorem, states that it is impossible for a distributed data system to simultaneously provide more than two out of the following three guarantees:

Consistency (C): Every read receives the most recent write or an error. In other words, all nodes in the system have the same data at any given time.

Availability (A): Every request receives a response, without guarantee that it contains the most recent write. This means the system is always operational and responsive, even if some nodes are down or partitioned (network partition).

Partition tolerance (P): The system continues to operate despite network partitions (communication failures) that may cause some messages to be lost or delayed between nodes

CP systems prioritize Consistency and Partition tolerance over Availability. They sacrifice availability when there is a network partition to ensure that data remains consistent across all nodes.

AP systems prioritize Availability and Partition tolerance over Consistency. They provide high availability even in the event of a network partition, accepting that there might be temporary inconsistencies between nodes.