The document critiques the CAP theorem, arguing that its definition of availability and consistency is too narrow. It suggests focusing instead on latency, service level agreements, and a spectrum of consistency options from linearizability to eventual consistency. Under certain network assumptions, all three of CAP - consistency, availability, and partition tolerance - can be achieved by prioritizing lower-latency coordination algorithms and distinguishing between local and global delays.

1. ACritiqueoftheCAPTheorem
A paper by Martin Kleppmann
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2. Disclaimer
Let’s have a discussion.
Ask questions.
Make comments.
Share ideas.
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3. TheBackground
The CAP Theorem in brief:
Pick two:
Consistency
Availability
Partition Tolerance
Formalized by Gilbert & Lynch in 2002.
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4. TheBeef
Technically, Gilbert & Lynch are correct, but…
What they proof is silly.
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5. The‘A’
Fox & Brewer say availability is a system-level concern. 👍
Gilbert & Lynch define it at an algorithm-level 👎:
“For a distributed system to be continuously available, every
request received by a non-failing node in the system must
result in a response”
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6. The‘C’
Brewer calls consistency a spectrum. 👍
Gilbert & Lynch define it as the most strict type of
consistency: linearizability 👎:
Linearizable distributed systems never allow for a stale
read.
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7. The‘P’
Partition tolerance means that a partition in the system (two
parts of the system cannot communicate with each other) can
be tolerated.
What do we mean? Finite or infinite partitions?
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8. Fair-lossLinks
A network link has the fair-loss property if the probability
of a message not being lost is non-zero, i.e. the link
sometimes delivers messages. The link may have intervals of
time during which all messages are dropped, but those
intervals must be of finite duration.
I.e. Not Byzantine, no deliberately malicious messages.
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9. TheSilliness
Gilbert & Lynch’s proof shows that you can only not have
linearizable and available distributed systems when there is
the possibility of infinite partitions.
If retry is possible, partitions are finite and latency is
not a concern, you can have all three: CAP.
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10. ABetterWay
Let's concentrate on latency and service level agreements,
not consistency and availability.
That means talking about delays..
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11. Delay-sensitivity
An algorithm is delay-sensitive if it need coordination to do
a read or write action.
Writes Reads
Linearizability
(e.g. The ‘I’ in ACID)
O(d) O(d)
Sequential Consistency
(e.g. Paxos, Sirius)
O(d) O(1)
Causal Consistency
(i.e. non-related data may
be out of order)
O(1) O(1)
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12. WANvs.LANDelays
A O(d) algorithm that only need coordination locally is
cheaper than one that need coordination globally:
O(dlocal) << O(dglobal)
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13. ANewThinking
Availability is empirical (SLAs)
Delay-sensitive means an algorithm must coordinate
Network Faults (not just partitions)
Fault Tolerance means when does it break (not infinite)
Consistency is a spectrum (linearizability to eventual)@trevmex

14. Conclusion
CAP was helpful in the beginning.
But we can do better.
Let’s start with delay-sensitivity and SLAs.
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