CAP定理是否意味着ACID对于分布式数据库来说是不可能的?[英] Does the CAP theorem imply that ACID is not possible for distributed databases?



nosql酸(分布式)数据库尽管CAP定理.这是怎么可能的? CAP定理与(可能/无法)酸是什么关系?

是不可能的,分布式计算机系统可以同时提供一致性, 可用性和分区耐受性.



在分布式系统中的A 分区期间,您必须在一致性和 availapial 中选择.





如果您想要更深入的解释,可以查看 a>, or ""> here .


paceLc定理延长了上限即使在Partitions ernaftions aren aren aents aren aren aents aren aents arents arents arents aren发生.分布式系统的令人兴奋的见解之一是,当使用筏或paxos之类的共识协议来创建事务日志时,可以将它们耐受地分配而不会失去一致性. calvin协议将筏日志与确定性交易应用程序结合在一起.

faunadb 即使在分区或复制失败期间,只要不划分复制品,就可以在分区或复制失败期间进行严格的序列化.



There are NoSQL ACID (distributed) databases, despite CAP theorem. How this is possible? What's the relation between CAP theorem and (possible/not possible of) being ACID?

Is impossible for a distributed computer system to simultaneously provide consistency, availability and partition tolerance.


CAP theorem is actually a bit misleading. The fact you can have a CA design is nonsense because when a partition occurs you necessarily have a problem regarding consistency (data synchronization issue for example) or availability (latency). That's why there is a more accurate theorem stating that :

During a partition in a distributed system, you must chose between consistency and availability.

Still in practice it is not that simple. You should note that the choice between consistency and availability isn't binary. You can even have some degree of both. For example regarding ACID, you can have atomic and durable transactions with NoSQL, but forfeit a degree of isolation and consistency for better availability. Availability can then be assimilated to latency because your response time will depend on several factors (is the nearest server available ?).

So, to answer your question, this is usually marketing bullshit. You need to actually scratch the surface to see what the solution is exactly gaining and forfeiting.

If you want deeper explanations you can look here, here or here.


The PACELC theorem extends CAP to talk about the tradeoffs even when partitions aren't happening. One of the exciting insights for distributed systems, is that they can be made partition tolerant without losing consistency, when consensus protocols such as RAFT or Paxos are used to create a transaction log. The Calvin protocol combines a RAFT log with deterministic transaction application.

FaunaDB implements Calvin, allowing it to maintain ACID transactions with strict-serializability, even during partitions or during replica failure, as long as a quorum of replicas is not partitioned.