CAP theorem
need to sacrifice consistency or availability in the presence of network partitions From Wikipedia, the free encyclopedia
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The CAP theorem, also known as Brewer's theorem, is a concept in distributed computing that outlines the trade-offs between three crucial properties—Consistency, Availability, and Partition Tolerance. Proposed by Eric Brewer around the year 2000, the CAP theorem asserts that, in a distributed data store, it is impossible to simultaneously guarantee all three of the following:
- Consistency: Every read operation in the system returns the most recent write. In other words, all nodes in the system have the same data at the same time.
- Availability: Every request to the system receives a non-error response, without any guarantee that it contains the most recent write. The system remains responsive even in the face of failures.
- Partition Tolerance: The system continues to operate despite the loss of messages or network partitions, ensuring that each node can operate independently.
The English used in this article or section may not be easy for everybody to understand. (December 2023) |
In a distributed system, network partitions (communication breakdowns between nodes) are inevitable. The CAP theorem acknowledges that, during a network partition, a choice must be made between providing consistency or availability. This led to the famous saying that in the event of a network partition, a system can either be "consistent and partition-tolerant (CP)" or "available and partition-tolerant (AP)."
The CAP theorem is a fundamental principle in designing and understanding distributed systems, influencing architects and engineers in making decisions about system trade-offs based on the specific requirements and priorities of their applications.
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