What is CAP Theorem?
CAP Theorem, also known as Brewer's theorem, is a concept that describes the trade-offs between consistency, availability, and partition tolerance in distributed systems. It states that it is impossible for a distributed system to simultaneously guarantee all three of these properties to the fullest extent.
History
The CAP Theorem was proposed by Eric Brewer in 2000 during the Symposium on Principles of Distributed Computing (PODC). The theorem was later proved by Seth Gilbert and Nancy Lynch of MIT in 2002.
Functionality and Features
CAP Theorem provides a framework for understanding the limitations of distributed systems. It implies that distributed systems must prioritize two of the three properties:
- Consistency: All nodes in a distributed system view the same data at the same time.
- Availability: The system remains operational and can respond to requests at all times.
- Partition Tolerance: The system continues to operate despite network failures.
Architecture
The architecture of distributed systems based on CAP Theorem depends on the prioritization of the properties. For example, if a system emphasizes consistency and availability, it might opt for synchronous replication, whereas a system focusing on availability and partition tolerance may use asynchronous replication.
Benefits and Use Cases
The CAP Theorem helps design resilient distributed systems. It empowers system architects to balance needs based on system requirements and business needs. It is especially useful in building large-scale systems where inevitable network partitioning and latency issues are a concern.
Challenges and Limitations
A challenge associated with CAP Theorem is that it forces architects to compromise on one of the properties. It is not always clear-cut, and the choices depend on the specific requirements of the use case.
Comparisons
CAP Theorem is often compared with PACELC Theorem, which extends CAP by considering the trade-offs between latency and consistency during normal operation and when a network partition occurs.
Integration with Data Lakehouse
In a data lakehouse arrangement, the CAP Theorem can be a helpful perspective when architecting data storage and processing layers. Depending on the priority, a lakehouse can be designed to emphasize consistency and availability, or availability and partition tolerance.
Security Aspects
While the CAP Theorem mainly concerns functional aspects of distributed systems, maintaining security requires additional measures not covered directly by the theorem.
Performance
The performance of a system based on CAP Theorem depends on the prioritized components. A system optimized for consistency and availability may exhibit strong performance in stable network conditions but might be vulnerable to network partitions.
FAQs
What does CAP Theorem mean for distributed systems? It provides an understanding of the trade-offs between Consistency, Availability, and Partition tolerance in distributed systems.
How does CAP Theorem benefit system architects? It helps them design resilient distributed systems by choosing two properties out of Consistency, Availability, and Partition tolerance based on needs.
Glossary
Consistency: Every read from the system returns the latest write.
Availability: Every request gets a response without any error.
Partition Tolerance: The system continues to operate despite partial network failure.
