CAP Theorem △

The CAP theorem states that distributed databases have to choose between consistency, availability, and partition tolerance. You can only pick two out of the three guarantees.

Consistency: all nodes see the same data at the same time. Strict consistency.
Availability: Every request receives a response. The system is always up.
Partition tolerance: The system continues to operate despite network partitions.

Implications

Can’t have all three guarantees in a distributed system
Sacrifice consistency for availability in partition-prone systems
Many NoSQL databases favor AP (availability and partition tolerance)
Traditional RDBMS favor CA (consistency and availability)
Understand tradeoffs when choosing databases

Examples

CP - Consistency and Partition Tolerance

Favors consistency over availability during a partition. Useful for systems that need strong consistency guarantees.


- Blockchain networks - need consistent ledger
- Multi-player games - need consistent state
- Financial transactions - need consistency guarantees

AP - Availability and Partition Tolerance

Favors availability over consistency during a partition.


- Web applications - need to serve users like retail websites.
- Real-time analytics - need uptime
- IoT backends - need availability for devices

CA - Consistency and Availability

No partitions allowed. Maintains both consistency and availability. Useful for systems that operate in a trusted network with no partitions expected.


- Legacy databases - no distributed partitions
- Intranet applications - controlled network

Bottom line

So in summary:

CP prioritizes consistency in distributed systems
AP prioritizes availability in partition-prone systems
CA works in a trusted non-distributed environment

Choose based on application requirements. The CAP theorem implies there are fundamental tradeoffs in distributed systems.

Sources

Educative.io