Eventual consistency

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Eventual consistency is a consistency model used in distributed computing to achieve high availability that informally guarantees that, if no new updates are made to a given data item, eventually all accesses to that item will return the last updated value.^[1] Eventual consistency, also called optimistic replication,^[2] is widely deployed in distributed systems and has origins in early mobile computing projects.^[3] A system that has achieved eventual consistency is often said to have converged, or achieved replica convergence.^[4] Eventual consistency is a weak guarantee – most stronger models, like linearizability, are trivially eventually consistent.

Eventually-consistent services are often classified as providing BASE semantics (basically-available, soft-state, eventual consistency), in contrast to traditional ACID (atomicity, consistency, isolation, durability).^[5][6] In chemistry, a base is the opposite of an acid, which helps in remembering the acronym.^[7] According to the same resource, these are the rough definitions of each term in BASE:

• Basically available: reading and writing operations are available as much as possible (using all nodes of a database cluster), but might not be consistent (the write might not persist after conflicts are reconciled, and the read might not get the latest write)
• Soft-state: without consistency guarantees, after some amount of time, we only have some probability of knowing the state, since it might not yet have converged
• Eventually consistent: If we execute some writes and then the system functions long enough, we can know the state of the data; any further reads of that data item will return the same value

Eventual consistency is sometimes criticized^[8] as increasing the complexity of distributed software applications. This is partly because eventual consistency is purely a liveness guarantee (reads eventually return the same value) and does not guarantee safety: an eventually consistent system can return any value before it converges.