What is the CAP Theorem?

The CAP theorem, also known as Brewer's theorem, states that it is impossible for a distributed data store to simultaneously provide more than two out of the following three guarantees: Consistency, Availability, and Partition Tolerance.

Can you explain Consistency, Availability, and Partition Tolerance?

Consistency means that all clients see the same data at the same time, no matter which node they connect to. Availability means that any client making a request for data gets a response, even if one or more nodes are down. Partition Tolerance means the system continues to work despite message loss or partial failure of the network.

System Design Interview

The CAP Theorem

Grasp the fundamental trade-offs in distributed systems. Learn how the CAP Theorem shapes the design of databases and other large-scale services.

Conceptual Example: CAP Theorem Trade-offs

This table illustrates how different types of databases prioritize the guarantees of the CAP theorem.

                            System Type      | Prioritizes | Example Databases
                            -------------------|-----------------|------------------------
                            CP (Consistent & Partition Tolerant) | Consistency over Availability | MongoDB, Redis
                            AP (Available & Partition Tolerant)  | Availability over Consistency | Cassandra, CouchDB
                            CA (Consistent & Available)        | Consistency and Availability (not partition tolerant) | Traditional RDBMS (e.g., PostgreSQL, MySQL) in a single-server setup
                        

Our AI Coach can help you discuss real-world scenarios and choose the right database for a given system design problem based on the CAP theorem trade-offs.