Add Availability vs consistency section

README.md

@@ -557,3 +557,37 @@ Generally, you should aim for **maximal throughput** with **acceptable latency**
 ### Source(s) and further reading
 
 * [Understanding latency vs throughput](https://community.cadence.com/cadence_blogs_8/b/sd/archive/2010/09/13/understanding-latency-vs-throughput)
+
+## Availability vs consistency
+
+### CAP theorem
+
+<p align="center">
+  <img src="http://i.imgur.com/bgLMI2u.png">
+  <br/>
+  <i><a href=http://robertgreiner.com/2014/08/cap-theorem-revisited>Source: CAP theorem revisited</a></i>
+</p>
+
+In a distributed computer system, you can only support two of the following guarantees:
+
+* **Consistency** - Every read receives the most recent write or an error
+* **Availability** - Every request receives a response, without guarantee that it contains the most recent version of the information
+* **Partition Tolerance** - The system continues to operate despite arbitrary partitioning due to network failures
+
+*Networks aren't reliable, so you'll need to support partition tolerance.  You'll need to make a software tradeoff between consistency and availability.*
+
+#### CP - consistency and partition tolerance
+
+Waiting for a response from the partitioned node might result in a timeout error.  CP is a good choice if your business needs require atomic reads and writes.
+
+#### AP - availability and partition tolerance
+
+Responses return the most recent version of the data, which might not be the latest.  Writes might take some time to propagate when the partition is resolved.
+
+AP is a good choice if the business needs allow for [eventual consistency](#eventual-consistency) or when the system needs to continue working despite external errors.
+
+### Source(s) and further reading
+
+* [CAP theorem revisited](http://robertgreiner.com/2014/08/cap-theorem-revisited/)
+* [A plain english introduction to CAP theorem](http://ksat.me/a-plain-english-introduction-to-cap-theorem/)
+* [CAP FAQ](https://github.com/henryr/cap-faq)