The CAP theorem states that a distributed system can only guarantee two out of three: Consistency, Availability, and Partition Tolerance at any given time.
What is the CAP Theorem?
Consistency means every read receives the most recent write or an error. All nodes show the same data at the same time, no matter where you connect.
Consistency Explained
Availability ensures every request gets a response, even if some nodes are down. The system always returns a result for queries, without exceptions.
Availability Defined
Partition tolerance means the system keeps working even if communication between nodes is lost or delayed. It’s essential for any distributed system.
Partition Tolerance
During network failures, you must choose: Consistency or Availability. You can’t have both with Partition Tolerance in place. It’s a fundamental design decision.
The Tradeoff
NoSQL databases like Cassandra favor Availability and Partition Tolerance (AP), while traditional RDBMS often choose Consistency and Availability (CA).
Real-World Examples
Understanding CAP helps you design systems that balance reliability, speed, and correctness-crucial for cloud apps, databases, and modern distributed architectures
Why It Matters