CAP theorem
The CAP Theorem states that, in a distributed system (a collection of interconnected nodes that share data.), you can only have two out of the following three guarantees across a write/read pair: Consistency, Availability and Partition Tolerance - one of them must be sacrificed.
- Consistency - Every read receives the most recent write or an error.
- Availability - Every request receives a response, without guarantee that it contains the most recent version of the information
- Partition Tolerance - The system will continue to function when network partitions occur.
Networks aren't reliable, so you'll need to support partition tolerance. You'll need to make a software tradeoff between consistency and availability.
CP - Consistency and partition tolerance
Waiting for a response from the partitioned node might result in a timeout error. CP is a good choice if your business needs require atomic reads and writes.
AP - availability and partition tolerance
Responses return the most readily available version of the data available on any node, which might not be the latest. Writes might take some time to propagate when the partition is resolved.
