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Strong read

A read that always returns the latest acknowledged write, at a higher cost.

Taught in Chapter 28: Consistency.

More from the same chapter

• CAP theorem: During a network partition, a store can stay consistent or available, not both.
• Causal consistency: If one change could have caused another, every copy shows them in that order; unrelated changes may appear in any order.
• Consistency model: What a store promises a read can return while copies catch up.
• Consistent prefix: Seeing changes in the order they happened, so a reply never shows up before the comment it answers.
• Linearizable: A store that behaves as if there were only one copy: every read returns the latest acknowledged write. The C in CAP.
• Monotonic reads: A promise that a user never sees data go back in time between reads.
• PACELC: Extends CAP: without a partition, the everyday trade is latency against consistency.
• Strict serializable: Serializable and linearizable at once: transactions behave as if run one at a time, in an order that matches real time.