cap-theorem

Distributed systems must handle network partitions (when nodes cannot communicate). Designers need a framework to reason about what properties a distributed system can guarantee under such failures.

The CAP Theorem states that a distributed data store can simultaneously provide at most two of three guarantees: Consistency (every read receives the most recent write or an error), Availability (every request receives a non-error response), and Partition Tolerance (the system continues operating despite arbitrary network failures). Since network partitions are inevitable, designers effectively choose between CP (Consistency + Partition Tolerance) and AP (Availability + Partition Tolerance).

1. Normal operation: All three properties are satisfied — nodes communicate, reads are consistent, responses are returned.
2. Partition occurs: Network failure splits nodes into groups that cannot communicate.
3. CP choice: The system refuses responses from nodes that cannot be confirmed as consistent — returns errors or timeouts until the partition heals.
4. AP choice: The system returns whatever data is available from reachable nodes, accepting that data may be stale. Writes are queued and merged when the partition resolves.

• C (Consistency): Every read receives the most recent write or an error
• A (Availability): Every request receives a (non-error) response, without guarantee it contains the latest write
• P (Partition Tolerance): The system continues to function despite network partitions
• P is mandatory in distributed systems — networks are unreliable by nature
• CA is a theoretical option that only applies to single-node systems or systems that can guarantee no network faults

• Builds into: CP — Consistency and Partition Tolerance
• Builds into: AP — Availability and Partition Tolerance
• Related: Strong Consistency — guaranteed in CP systems
• Related: Eventual Consistency — used in AP systems

• PACELC extension: CAP only considers partitions. PACELC adds that even without a partition (Else), there’s a latency-consistency trade-off. Most systems don’t operate in partition mode.
• CA is misleading: Single-node systems aren’t distributed. Therefore, real distributed systems are either CP or AP.
• Partition recovery is not automatic: When a partition heals, reconciliation logic is needed — stale writes may conflict, and resolution strategies (last-write-wins, CRDTs, etc.) must be in place.