Notes on Replicated Data Consistency Explained Through Baseball

In the December 2013 issue of Communications of the ACM, Doug Terry examines an intermediate level of consistency of data in Replicated Data Consistency Explained Through Baseball (pp. 82-89).

Table 1, on p.84, lists six (6) consistency guarantees:

Strong Consistency See all previous writes
Eventual Consistency See a subset of previuos writes
Consistent Prefix See initial sequence of writes
Bounded Staleness See all “old” writes
Monotonic Reads See increasing subset of writes
Read My Writes See all writes performed by reader

Terry classifies the consistency, performance, and availability trade-offs for each of these consistency guarantees in Table 2 (p.85):

Guarantee Consistency Performance Availability
Strong Consistency excellent poor poor
Eventual Consistency poor excellent excellent
Consistent Prefix okay good excellent
Bounded Staleness good okay poor
Monotonic Reads okay good good
Read My Writes okay okay okay

Terry concludes:

  • All of the six presented consistency guarantees are useful
  • Different clients may want different consistencies even when accessing the same data
  • Even simple databases may have diverse users with the different consistency needs
  • Clients should be able to choose desired consistency

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