How does cloud computing handle data consistency?

What are the main challenges of data consistency in cloud computing?

The main challenges include network latency, distributed data storage, and the CAP theorem, which states that you can only achieve two of the three guarantees: consistency, availability, and partition tolerance.

How do cloud providers ensure data consistency?

Cloud providers use various techniques like data replication, consensus algorithms, and eventual consistency models to ensure data consistency across distributed systems.

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 of the following three properties: Consistency, Availability, and Partition Tolerance. This means that if a network partition occurs, you must choose between consistency and availability.

What is eventual consistency?

Eventual consistency is a model where updates to a distributed system will eventually propagate to all nodes, ensuring that all copies of the data will become consistent over time, but not immediately.