CAP only talks about the uncommon unhappy path (given a network partition, what is tradeoff between availability and consistency). PACELC theorem builds on CAP to describe that even in the absence of a network partition, there is a trade-off between latency and consistency (in other words, describing the tradeoffs associated with BOTH the common happy path and uncommon unhappy path).

Azure Cosmos DB offers 5 well-defined consistency models for you to choose from, so that you can choose the right tradeoffs for a given application or scenario. This way, you aren't stuck choosing between the hard extremes of Strong and Eventual consistency.

See: https://docs.microsoft.com/en-us/azure/documentdb/documentdb...

As the Cosmos DB SLA doc describes, for any of the 5 consistency models the service supports, the service guarantees all the other three guarantees (latency at the 99th percentile, availability and throughput) at 99.99%. One of the benefits of well-defined consistency models is that for a given model, developers can clearly make the tradeoffs between (1) latency vs. consistency, (2) availability vs. consistency and (3) throughput vs. consistency. The service documentation covers some of these tradeoffs.

See (1) https://docs.microsoft.com/en-us/azure/documentdb/documentdb... and (2) https://docs.microsoft.com/en-us/azure/documentdb/documentdb... (also check out the references at the end of the page)