Design Microservices Architecture with Patterns and Principles - CAP Theorem

The video tutorial explains the CAP theorem, which states that in a distributed system, consistency, availability, and partition tolerance cannot all be achieved simultaneously. It delves into each concept: consistency ensures data integrity, availability ensures system responsiveness, and partition tolerance allows the system to function despite network issues. The tutorial highlights the importance of partition tolerance in distributed architectures and discusses how NoSQL databases like MongoDB and Cassandra prioritize partition tolerance while balancing consistency and availability.

What does the CAP theorem state about distributed systems?

• They are always consistent and available.

• They can only achieve two out of three: consistency, availability, and partition tolerance.

• They must choose between consistency and availability.

• They can achieve all three: consistency, availability, and partition tolerance.

What is the primary focus of consistency in distributed systems?

• Maximizing the speed of data retrieval.

• Allowing the system to operate despite network failures.

• Ensuring data is always available.

• Guaranteeing that all nodes see the same data at the same time.

How does availability affect a distributed system?

• It ensures the system is always operational and responsive.

• It guarantees data consistency across all nodes.

• It reduces the need for data replication.

• It allows the system to handle network partitions.

Why is partition tolerance crucial in distributed systems?

• It allows the system to continue operating despite network partitions.

• It ensures data is always consistent.

• It reduces the complexity of the system.

• It maximizes data availability.

Which two properties do NoSQL databases like MongoDB and Cassandra prioritize?

• Consistency and availability

• Consistency and partition tolerance

• Availability and partition tolerance

• Scalability and security