We discussed CAP theorem in our previous article here. Now let’s discuss an extension of the CAP theorem — PACELC theorem. The first three letters of PAC are the same in CAP — Consistency, Availability, and Partition Tolerance. The rest — ELC stands for Else[E], even if the system runs usually, choose between Latency[L] and Consistency[C] of a replicated system. The theorem looks like we maintained high availability by replication.

The question here is why we need PACELC since the CAP theorem works a charm even when there are network partitions. But PACELC is an answer when we raise a question on CAP theorem — “What will happen to a distributed system if there are no network partitions?”.

There are the following things that the PACELC theorem states about a system that replicates data.

1. If statement

When there is a partition in a distributed system, the tradeoff between availability and consistency is done.

2. Else statement

When there is no partition and the system is running normally in a distributed system, the tradeoff between latency and consistency is done.

The examples to choose consistency and giving up availability alongside lower latency [PA/EC] are BigTable and HBase. MongoDB is also one of the examples of PA/EC since it goes for availability when there is a partition but chooses a partition in all the other cases. Likewise, to choose availability over consistency after the partition [PA/EL] are Dynamo and Cassandra. Else, they get on with lower latency.

Advantages of PACELC over CAP Theorem

• Unlike the CAP theorem, PACELC considers latency and consistency as a tradeoff.

• We can effectively use it to choose and design distribution systems.

• It can get over the major downfalls of the CAP theorem.

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