How does the CAP theorem affect database design?

Can you explain the CAP theorem and its significance in database design?

The CAP theorem states that in a distributed data store, you can only guarantee two of the following three properties: Consistency, Availability, and Partition Tolerance. This means that when designing a database, you must prioritize which two properties are most important for your application.

How do I decide which two properties to prioritize?

It depends on your application's requirements. For example, if you need real-time data access, you might prioritize Availability and Partition Tolerance. If data accuracy is critical, you might choose Consistency and Partition Tolerance.

Can you give me an example of a database that prioritizes availability?

Sure! Amazon DynamoDB is a great example. It prioritizes Availability and Partition Tolerance, allowing it to handle large amounts of traffic while still being accessible.

What are the trade-offs of prioritizing consistency?

Prioritizing Consistency often leads to reduced Availability, especially during network partitions. This means that some users may not be able to access the data until the system can ensure that all nodes are consistent.