CAP Theorem

CAP Theorem states that a distributed system can only guarantee two of three properties simultaneously.

The Three Properties

Consistency (C)

Every read receives the most recent write or an error.

Availability (A)

Every request receives a response (not necessarily the latest data).

Partition Tolerance (P)

The system continues to operate despite network partitions.

CAP Trade-offs

CP Systems → Sacrifice Availability
  Examples: HBase, MongoDB (strong mode), Zookeeper

AP Systems → Sacrifice Consistency
  Examples: Cassandra, CouchDB, DynamoDB

CA Systems → Not realistic in distributed systems
  (Can't avoid network partitions)

Practical Implications

System	Choice	Use Case
Cassandra	AP	High availability writes
HBase	CP	Strong consistency needed
DynamoDB	AP (default)	Eventually consistent

PACELC Extension

PACELC extends CAP by also considering Latency vs Consistency tradeoffs during normal operation.

Conclusion

Understanding CAP helps engineers choose the right database for their consistency and availability requirements.