CouchDB: The Definitive Guide

Chapter 2. Eventual Consistency

In the previous chapter, we saw that CouchDB’s flexibility allows us to evolve our data as our applications grow and change. In this chapter, we’ll explore how working “with the grain” of CouchDB promotes simplicity in our applications and helps us naturally build scalable, distributed systems.

Working with the Grain

A distributed system is a system that operates robustly over a wide network. A particular feature of network computing is that network links can potentially disappear, and there are plenty of strategies for managing this type of network segmentation. CouchDB differs from others by accepting eventual consistency, as opposed to putting absolute consistency ahead of raw availability, like RDBMS or Paxos. What these systems have in common is an awareness that data acts differently when many people are accessing it simultaneously. Their approaches differ when it comes to which aspects of consistency, availability, or partition tolerance they prioritize.

Engineering distributed systems is tricky. Many of the caveats and “gotchas” you will face over time aren’t immediately obvious. We don’t have all the solutions, and CouchDB isn’t a panacea, but when you work with CouchDB’s grain rather than against it, the path of least resistance leads you to naturally scalable applications.

Of course, building a distributed system is only the beginning. A website with a database that is available only half the time is next to worthless. Unfortunately, the traditional ...