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MENTAL MODEL · M2099

CAP Theorem / Brewer's Theorem

CAP Theorem / Brewer's Theorem
SystemsHigh supportSystems Theory
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Version 1.0.0 · Updated 2026-07-30

CORE DEFINITION

In a distributed system (such as blockchain, cloud database), it is impossible to satisfy all three of the following simultaneously; at most, you can choose two out of three: 1. Consistency: All nodes see the same data at the same time. 2. Availability: The system responds to every request (does not crash). 3. Partition Tolerance: The system continues to operate even if network failures prevent nodes from communicating.

SCAFFOLDING EFFECT

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Reduce cognitive load

In theoretical computer science, the CAP theorem, also known as Brewer's theorem, states that it is impossible for a distributed computing system to simultaneously satisfy the following three guarantees: Consistency: All nodes access the same latest data copy. Availability: Every request receives a non-error response, but without guarantee that the data is the latest. Partition tolerance: In effect, partition refers to a time limit on communication. If the system cannot achieve data consistency within the time limit, it means a partition has occurred, and a choice must be made between C and A for the current operation. The simplest way to understand CAP is to imagine two nodes on opposite sides of a partition. Allowing...

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Based on the 'distributed impossible trinity'. Network partitions (P) are inevitable, so in practice, there is a trade-off between C and A; during a partition, either choose consistency (sacrificing availability) or availability (sacrificing consistency).

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Source support: Explicit

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    zh.wikipedia.orghttps://zh.wikipedia.org/wiki/CAP%E5%AE%9A%E7%90%86ZH · Explicit
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