CAP Theorem Explained

Re:CAP Theorem Explained by rg81 on Thursday June 19, 2014 @09:29AM (#7915908)

There's some debate on the Elasticsearch forums around CA vs. CP - with the overall consensus in favor of CA. Elasticsearch doesn't perform well across networks so in practice, most deployments have multiple nodes in a single datacenter - CA.

Thanks for your feedback though, I have some posts queued up on more of the subtleties in the model, this was just meant to be an introductory post.

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Re:CAP Theorem Explained by kainosnoema on Thursday June 19, 2014 @12:21PM (#7916885)

Elasticsearch actually sacrifices both consistency and availability during partitions, even when inside a single datacenter (trust me, they happen in production).

If you configure ES to prioritize consistency somewhat (minimum_master_nodes), it prevents writes during a partition—but there's at least one "split" partition scenario where even minimum_master_nodes doesn't prevent inconsistent writes. If you configure ES to prioritize availability during a partition, it isn't consistent. Remember, ES doesn't claim to be consistent and doesn't even use any sort of consensus algorithm.

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Re:CAP Theorem Explained by room271 on Thursday June 19, 2014 @01:09PM (#7917141)

I feel like my original comment was a bit harsh so thanks for replying.

Re: the debate about CA vs CP, I've seen this too, but I think it reflects confusion rather than genuine options. The 'P' of CAP takes effect whenever you have two or more processes which clients can communicate with. So even if you are running within the same datacenter when using ES, provided clients can communicate with more than one ES node, CAP still applies.

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