What types of data consistency levels exist in distributed architectures?

In distributed systems, there are different levels of data consistency, which determine how quickly and in what manner data changes become visible to all nodes. The main types of consistency:

• Strong consistency: After a write, data is immediately visible to all clients. It is guaranteed that all reads after the write will return the updated data.

• Weak consistency: There are no guarantees that other nodes will see the changes immediately after a write. Data may be outdated for some time.

• Eventual consistency: Ultimately, all nodes will reach the same state, but at the moment of reading, data may differ.

• Read-your-writes consistency: The client sees its own changes immediately, but other clients may see outdated data.

• Session consistency: Within a session, the client sees sequential updates, but there may be delays outside the session.

The choice of consistency level depends on system requirements: strong consistency ensures accuracy but reduces performance and scalability, while weak consistency is the opposite.