The CAP Theorem, also known as Brewer's Theorem, is a fundamental principle in the field of distributed systems. It states that in the presence of a network partition (P), a distributed system can only guarantee either Consistency (C) or Availability (A), but not both simultaneously. Here’s a detailed breakdown of the three properties involved:
Consistency (C): Every read receives the most recent write or an error. This means that all nodes in the system reflect the same data at any given time, ensuring that any read operation returns the latest written data.
Availability (A): Every request receives a (non-error) response, without the guarantee that it contains the most recent write. This implies that the system is always operational and can respond to read and write requests, but the data returned might not be the most up-to-date.
Partition Tolerance (P): The system continues to operate despite an arbitrary number of messages being dropped (or delayed) by the network between nodes. This means that the system can handle network failures that prevent some nodes from communicating with others.
The theorem essentially highlights the trade-offs that must be made when designing distributed systems. In the event of a network partition, a system must choose between being consistent or being available. It is impossible to achieve all three properties (Consistency, Availability, and Partition Tolerance) simultaneously in a distributed system.
For example, if a network partition occurs:
A CP (Consistency and Partition Tolerance) system will ensure that all nodes have the same data, but some requests might not be processed ...
