The CAP theorem has become one of the hottest theorems in recent years; when discussing distributed systems, CAP is inevitably mentioned. However, I feel that I haven’t thoroughly understood it, so I wanted to write a blog post to record my understanding. I will update the content as I gain new insights.

Understanding

I read the first part of this paper.

The CAP theorem [Bre12] says that you can only have two of the three desirable properties of:

• C: Consistency, which we can think of as serializability for this discussion;
• A: 100% availability, for both reads and updates;
• P: tolerance to network partitions.

This leads to three kinds of systems: CA, CP and AP, based on what letter you leave out.

Let me share my understanding, using a network composed of three machines (x, y, and z) as an example:

• C (Consistency): The three machines appear as one. Operations of addition, deletion, modification, and query on any one machine should always be consistent. That is, if you read data from x and then read from y, the results are the same. If you write data to x and then read from y, you should also read the newly written data. Wikipedia also specifically mentions that it’s acceptable to read the data just written to x from y after a short period of time (eventual consistency).

• A (Availability): The three machines, as a whole, must always be readable and writable; even if some parts fail, it must be readable and writable.

• P (Partition Tolerance): If the network between x, y, and z is broken, any machine cannot or refuses to provide services; it is neither readable nor writable.

Here, C is the easiest to understand. The concepts of A and P are somewhat vague and easy to confuse.

Now let’s discuss the three combinations:

If the network between x, y, and z is disconnected:

• CA: Ensure data consistency (C). When x writes data, y can read it (C). Allow the system to continue providing services—even if only x and y are operational—ensuring it is readable and writable (A). We can only tolerate z not providing service; it cannot read or write, nor return incorrect data (losing P).

• CP: Ensure data consistency (C). Allow all three machines to provide services (even if only for reads) (P). We can only tolerate that x, y, and z cannot write (losing A).

• AP: Allow all three machines to write (A). Allow all three machines to provide services (reads count) (P). We can only tolerate that the data written by x and y doesn’t reach z; z will return data inconsistent with x and y (losing C).

CA is exemplified by Paxos/Raft, which are majority protocols that sacrifice P; minority nodes remain completely silent. CP represents a read-only system; if a system is read-only, whether there’s a network partition doesn’t really matter—the tolerance to network partitions is infinitely large. AP is suitable for systems that only append and do not update—only inserts, no deletes or updates. Finally, by merging the results together, it can still function.