What are the challenges of distributed consistency?

What are the main challenges of achieving distributed consistency?

The main challenges include network latency, partition tolerance, and the CAP theorem, which states you can only have two of the three: consistency, availability, and partition tolerance.

Can you explain the CAP theorem in more detail?

Sure! The CAP theorem states that in a distributed data store, you can only guarantee two out of the following three properties: Consistency (all nodes see the same data at the same time), Availability (every request receives a response), and Partition Tolerance (the system continues to operate despite network partitions).

How do different databases handle these challenges?

Different databases use various strategies. For example, some prioritize consistency over availability, like traditional SQL databases, while others, like NoSQL databases, may prioritize availability and partition tolerance.

What are some real-world examples of these challenges?

Real-world examples include issues faced by companies like Facebook and Google during outages, where data consistency was compromised due to network partitions.