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Jan 4
“Eventually consistent semantics provide almost no guarantees regarding the recency of data returned (unbounded staleness of versions). Despite these weak guarantees, many data store users opt for eventual consistency in practice—why? It’s often faster to contact fewer replicas, and it’s also more available. However, instead of relying on anecdotal evidence, we should quantify why eventual consistency is “good enough” for many users. We can predict the expected consistency of an eventually consistent data store using models we’ve developed, called Probabilistically Bounded Staleness. It turns out that, in practice, and in the average case, eventually consistent data stores often deliver consistent data. Using PBS predictions, we can optimize the trade-off between latency and consistency and better understand why so many data store users choose eventual consistency.”

Probabilistically Bounded Staleness

"How eventual is eventual consistency? How consistent is eventual consistency? PBS provides answers to these questions using new techniques and simple modeling. Find out how and play with models in your browser on this page."

nice HTML5-based adjustable graph with a bunch of knobs for things like tolerable staleness, accuracy, replica configuration, etc. tweak away!

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