The CAP Theorem (or Brewer’s Theorem) was developed in response to a shift toward more distributed systems (Brewer, 2000). The theorem asserts that a distributed system cannot comply with all parts of ACID at all time. The larger the system, the lower the compliance. A distributed system must instead trade-off between properties.

• Consistency: The system must operate as designed and expected at all times.
• Availability: The system must be available when requested and must respond to each request.
• Partition Tolerance: The system must be able to continue operations during occasions of data loss or partial system failure.

The CAP Theorem states that at most two of the three properties can exist in any shared-data system. This is usually stated with a ‘pick two’ statement, illustrated in this figure.

An interesting use of this theorem drives the Lambda Architecture design discussed in Chapter 14. Lambda Architecture uses two paths for data: a Speed path where availability and partition tolerance are most important, and a Batch path where consistency and availability are most important.