What are consistency models in distributed systems?

What are consistency models in distributed systems?

Consistency models define the rules for how data is shared and updated across distributed systems. They ensure that all nodes see the same data at the same time.

Can you explain the difference between strong and eventual consistency?

Strong consistency guarantees that all reads return the most recent write, while eventual consistency allows for temporary discrepancies, ensuring that all nodes will eventually converge to the same value.

What are some examples of systems that use these models?

Examples include databases like Google Spanner, which uses strong consistency, and Amazon DynamoDB, which often employs eventual consistency.

How do these models affect system performance?

Stronger consistency models can lead to higher latency and reduced availability, while weaker models may improve performance but at the cost of immediate data accuracy.