Consistency models (strong, eventual) in HLD - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is strong consistency in distributed systems?

Strong consistency means that after a write completes, all reads will see that write immediately. It's like everyone always sees the latest version of data, no matter which server they ask.

beginner

Define eventual consistency.

Eventual consistency means that if no new updates happen, all copies of data will become the same eventually. But right after a write, some reads might see old data for a while.

beginner

Give a real-life example to explain strong consistency.

Imagine a bank account balance. If you deposit money, strong consistency means every teller and ATM immediately shows the new balance to everyone.

intermediate

Why might a system choose eventual consistency over strong consistency?

Because eventual consistency allows faster responses and better availability by letting some servers be temporarily out of sync. It's useful when perfect up-to-date data is not critical.

intermediate

What is a common tradeoff between strong and eventual consistency?

Strong consistency gives up some speed and availability to ensure all users see the same data immediately. Eventual consistency gives up immediate accuracy to gain speed and availability.

Which consistency model guarantees that all reads see the latest write immediately?

A Weak consistency

B Strong consistency

C Causal consistency

D Eventual consistency

Strong consistency ensures all reads reflect the most recent write immediately.

In which consistency model can reads temporarily return stale data after a write?

A Eventual consistency

B Strong consistency

C Linearizability

D Sequential consistency

Eventual consistency allows temporary stale reads but guarantees data will converge eventually.

Which is a benefit of eventual consistency?

A Simpler programming model

B Immediate data accuracy

C Higher availability and performance

D No data conflicts

Eventual consistency improves availability and performance by allowing temporary data divergence.

Strong consistency is most important for which type of application?

A Social media feeds

B Video streaming

C Caching static content

D Banking transactions

Banking requires accurate, up-to-date data, so strong consistency is critical.

What does eventual consistency guarantee if no new updates occur?

A Data will converge to the same value

B Data will remain inconsistent

C Data will be lost

D Data will be immediately consistent

Eventual consistency guarantees that all replicas will converge to the same data eventually.

Explain the difference between strong consistency and eventual consistency using a simple analogy.

Think about how quickly everyone sees an update in different situations.

Describe scenarios where eventual consistency is preferred over strong consistency and why.

Consider tradeoffs between accuracy and performance.