Inconsistency Resolution in Distributed Systems: Versioning

Modern distributed databases such as Amazon DynamoDB and Apache Cassandra replicate data across multiple servers to improve scalability, fault tolerance, and availability . However, replication introduces a major challenge: data inconsistency during concurrent updates . To address this problem, distributed systems use a technique called versioning . In this article, we’ll explore why versioning is needed, how it works, and how it helps resolve conflicts in eventually consistent systems. Why Versioning Is Needed In an eventually consistent system , updates do not reach all replicas at the same time due to network delays or partitions . Consider a system with three replicas: N = 3 Replicas: s0, s1, s2 Two clients update the same key at the same time: Client A → put(key1 = 10) Client B → put(key1 = 20) Because of network delays, the replicas may temporarily store different values : s0 = 10 s1 = 20 s2 = 10 Now the system contains conflicting values for the same key . This situation is call