Linearizability
Also known as: strong consistency, atomic consistency
Linearizability is the strongest single-object consistency model: every operation appears to take effect instantaneously at some point between its invocation and its response, and once a write is visible to any client it is visible to all. It makes a replicated store behave like a single copy.
Last reviewed · Part of the Architecture Glossary
In practice
Linearizability is a recency guarantee about one object. Serializability is an ordering guarantee about multi-object transactions. They are orthogonal axes, and conflating them is the most common mistake in this whole area — "strictly serializable" is the model that gives you both.
The test is simple: if client A's write completes at 10:00:00.000, can client B read the old value at 10:00:00.001? Under linearizability, no. Under anything weaker, yes.
What it costs: at least one round trip to a quorum on every read, or reads served only by the leader. Cross-region, that is 30–150 ms of unavoidable latency per operation — the PACELC "else latency" term made concrete.
Systems that offer it: etcd, ZooKeeper, Spanner (TrueTime), DynamoDB with ConsistentRead, single-leader Postgres reads on the primary.
When it matters
Distributed locks, leader election, uniqueness constraints, sequence generation, and any read that gates a decision the user immediately acts on — "did my payment go through?"
Common mistake
Turning on strong reads globally because it sounds safer. Most reads in a product are display reads that tolerate 200 ms of staleness. Paying quorum latency on all of them to protect the 2% that genuinely need it is how a system ends up slow everywhere and no more correct where it counts.
See also
- Eventual ConsistencyEventual consistency guarantees only that if writes stop, all replicas eventually converge to the same value.
- Serializable IsolationSerializable isolation guarantees that concurrent transactions produce the same result as some serial execution of them.
- CAP TheoremThe CAP theorem states that when a network partition occurs, a distributed system must choose between consistency (every read sees the latest write) and availability (every request gets a non-error response).
- QuorumA quorum is the minimum number of replicas that must respond for an operation to count.