What is eventual consistency and in what scenarios is it acceptable?

• A. Eventual consistency guarantees immediate, fresh reads after each write.
• B. Eventual consistency means reads may see stale data temporarily.
• C. Eventual consistency means updates propagate asynchronously; acceptable for social feeds, shopping carts, where strict immediacy is not required.
• D. Eventual consistency requires a single central server to coordinate updates.

Answer: (C)

Eventual consistency is a distributed-systems approach where updates are propagated to replicas asynchronously. Reads may return slightly older data for a short time, but if no new writes occur, all replicas will eventually converge to the same state. This style trades immediate, fresh reads for high availability and low latency across distributed nodes.

It's particularly suitable when immediate immediacy isn't critical—like social feeds, where you can see new posts after a short delay, or shopping carts, where updates on one device may take a moment to reflect on another. In these scenarios, the system stays responsive and available even during network partitions or delays.

If you need every read to reflect the most recent write right away, a stronger, tighter consistency model would be more appropriate, but eventual consistency shines when tolerance for a moment of stale data is acceptable.