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, sacrificing some Consistency. Conversely, 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! A common example is Amazon DynamoDB, which is designed to be highly available and partition-tolerant, allowing for quick access to data even during network partitions.

What are the trade-offs of prioritizing consistency?

Prioritizing consistency can lead to reduced availability, especially during network failures. Users may experience delays or unavailability of data until the system can ensure that all nodes are synchronized.