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Eventual consistency is a consistency model used in distributed systems to achieve high availability and partition tolerance. In this model, writes to any replica are allowed to succeed locally and are propagated to other replicas asynchronously. The system guarantees that, in the absence of further updates, all replicas will converge to the same value. However, there is no guarantee of immediate consistency after a write; reads may return stale data, and different replicas may temporarily disagree.

To reconcile differences, systems rely on anti-entropy processes, read repair, and hinted handoffs. Versions are typically labeled with vector clocks or timestamps, and conflicts may be resolved automatically (for example by last-writer-wins) or deferred to applications. Conflict-free replicated data types (CRDTs) provide mergeable data structures that help reduce the need for coordination in some cases.

Eventual consistency prioritizes availability and partition tolerance, as described by the CAP theorem. It allows operation during network partitions but introduces the risk of stale reads and temporary write conflicts. Deployment often includes tunable consistency levels, such as read repair, or quorum-based reads and writes, to balance latency, throughput, and data accuracy. Common use cases include large-scale web applications, content caches, session data, and other workloads where perfect immediacy is less critical. Notable implementations include Dynamo-style stores and databases such as Cassandra, Riak, and Couchbase, as well as systems that rely on CRDTs. Observability concerns include monitoring convergence, detecting conflicts, and testing the chosen consistency model.