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What is the essence of the CAP theorem?
sobes.tech AI
Answer from AI
The CAP theorem (Consistency, Availability, Partition Tolerance) states that in a distributed system, only two of the three properties can be guaranteed simultaneously:
- Consistency: All nodes see the same data at the same time. If data is changed on one node, this change is immediately reflected on all others.
- Availability: The system guarantees that each request receives a response (not an error). Any working node can process requests.
- Partition Tolerance: The system continues to operate even if network issues cause a partition into several isolated clusters, and nodes cannot communicate with each other.
During network partitioning, the system must choose between consistency and availability:
- CP system: Prefers Consistency over Availability. During partitioning, the system may become unavailable to ensure that all accessible nodes see consistent data. Write requests may be rejected.
- AP system: Prefers Availability over Consistency. During partitioning, the system remains accessible, but data may be inconsistent between partitions. After the partition is resolved, data should be synchronized.
- CA system: Theoretically exists but cannot exist in real network conditions where partitions are inevitable. In a distributed system, Partition Tolerance must always be considered.
The CAP theorem does not claim that a system cannot be made consistent and available under normal conditions without partitions. It specifically applies during network partitions.
When choosing between Consistent and Available in the context of Partition Tolerance, the decision depends on system requirements:
- Banking systems, where data accuracy is crucial, often choose CP.
- Social media platforms or online stores, where continuous availability is important, even with some delay in data synchronization, often choose AP.