CAP theorem is simple if we all use the same definitions. CAP follows from the requirements for nodes in distributed systems to send and receive messages before responding if the system requires atomic consistency. If the system can't pass messages, it can't be consistent. If consistency is a requirement, then losing messages implies the system cannot respond. These properties apply to any distributed systems.

1. Consistency…!
Availability…!
Messages…!
& You…

2. AP!
C
theorem

3. ant
ACID Compli
Consistent
“…as if every request was executing on a single
node, responding to operations one at a time.”

4. Available
“…every request received by a non-failing node
in the system must result in a response.”

5. Partition Tolerant
“…the network will be allowed to lose arbitrarily
many messages sent from one node to another”

6. Pick Any Two!?!!
It’s complicated…

7. Consistent & Partition Tolerant
“…it is easy to achieve atomic data and partition
tolerance. The trivial system that ignores all
requests meets these requirements.”

8. Consistent & Available
“If there are no partitions, it is clearly possible to
provide atomic, available data.”

9. Available & Partition Tolerant
“If there are no consistency requirements, the
service can trivially return v0, the initial value, in
response to every request.”

10. t-Connected Consistent
2 ⋅ t message + t local

11. What has been
neglected?
 Latency
 Failure
 Computation
 Durability
 More™

12. Latency
Petite Partitions
the little deaths

13. When the available consistency exceeds the
required availability a choice must be made…

14. Raising the question, how are business
decisions made?

16. What protocols are used
to pass messages in
your organization?

18. n
H as your organizatio
chosen consistent, available
or pa rtition tolerant?

19. In any human interaction, the required
amount of communication is inversely
proportional to the level of trust…
@bhorowitz

20. Andrew Clay Shafer
@littleidea
work on stuff that matters