What is consistency in the CAP theorem?

Can you explain what consistency means in the context of the CAP theorem?

Sure! In the CAP theorem, consistency means that every read receives the most recent write or an error. This ensures that all nodes in a distributed system reflect the same data at the same time.

How does consistency affect system performance?

Consistency can impact performance because achieving strong consistency often requires coordination between nodes, which can introduce latency. Systems may sacrifice consistency for availability or partition tolerance.

What are the trade-offs between consistency and availability?

The trade-off is that if a system prioritizes consistency, it may become unavailable during network partitions. Conversely, if it prioritizes availability, it might serve stale data.

Can you give examples of systems that prioritize consistency?

Yes! Examples include traditional relational databases like PostgreSQL and systems like etcd, which ensure strong consistency.

What is eventual consistency?

Eventual consistency is a model where updates to a distributed system will eventually propagate to all nodes, but not immediately. This allows for higher availability and partition tolerance.