CAP Theorem (Consistency, Availability, Partition Tolerance)

CAP theorem states it is impossible for a distributed system to simultaneously provide more than two of these three guarantees: consistency, availability and partition tolerance.

Consistency - means all clients see same data at same time no matter which node they connect to

Availability - means any client which requests data will get a response even if some nodes are down

Partition Tolerance - means system continues to operate despite network partitions. Partition indicates a communication break between two nodes.

Real-world distributed systems

In a distributed system, partitions cannot be avoided, so we must choose between consistency and availability.

ACID Properties (Atomicity, Consistency, Isolation, Durability)

ACID properties are typically associated with traditional relational databases and ensure the reliability and integrity of transactions.

Atomicity: Transactions are atomic, meaning they are treated as a single, indivisible unit. Either all the operations in a transaction are completed, or none of them are. There is no partial completion of a transaction.

Consistency: Transactions bring the database from one valid state to another. The database must satisfy a set of integrity constraints before and after the transaction.

Isolation: Transactions operate independently of each other. The execution of one transaction is isolated from the execution of others, ensuring that the concurrent execution of transactions produces a result that is equivalent to some serial execution.

Durability: Once a transaction is committed, its changes to the database are permanent and survive subsequent system failures.

Summary

In summary, while CAP and ACID address different concerns (distributed systems vs. database transactions), they highlight important trade-offs in system design. Systems need to be carefully designed based on the specific requirements and priorities of the application or use case.