In a distributed transaction system, what is the CAP theorem concerned with?

The CAP theorem, formulated by computer scientist Eric Brewer, addresses the trade-offs that distributed systems face concerning three critical properties: Consistency, Availability, and Partition tolerance.

Consistency ensures that every read operation receives the most recent write for a given piece of data, maintaining a single version of the truth across the system. This means that when a transaction is completed, all nodes in the distributed system see the same data.

Availability guarantees that every request receives a response, either successfully with the data or an error message, regardless of the state of the system's nodes. This ensures that the system remains operational and responsive at all times.

Partition tolerance refers to the capability of the distributed system to continue functioning even when network partitions occur, meaning some nodes can't communicate with others. The system must still maintain its operations as much as possible despite these disruptions.

The CAP theorem states that a distributed system can satisfy only two of the three guarantees at the same time. Understanding this theorem is crucial for architects and engineers to design robust distributed applications that balance these properties according to the specific needs and requirements of their systems.