What are the trade-offs of eventual consistency in distributed systems?

What are the trade-offs of eventual consistency in distributed systems?

Eventual consistency allows for high availability and partition tolerance, but it can lead to stale data and conflicts.

Can you explain how it differs from strong consistency?

Sure! Strong consistency ensures that all reads return the most recent write, while eventual consistency allows for temporary discrepancies.

What are some real-world examples of systems using eventual consistency?

Examples include Amazon DynamoDB and Apache Cassandra, which prioritize availability and partition tolerance.

How do developers handle conflicts in eventually consistent systems?

Developers often use conflict resolution strategies like last-write-wins, versioning, or application-level reconciliation.

Is eventual consistency suitable for all applications?

Not necessarily. It's best for applications where availability is critical and temporary inconsistencies are acceptable.