Building Event-Driven Microservices, 2nd Edition

Chapter 16. Eventual Consistency

Note

An earlier version of this chapter previously appeared in Building an Event-Driven Data Mesh (O’Reilly, 2023).

Eventual consistency is often a primary concern with distributed systems. For event-streams, eventual consistency concerns tend to lie mostly on the consumer side, as each consumer reads and processes events at their own rate.

Fortunately for us, there are some who have been looking at, working on, and thinking about eventual consistency for quite a long time. Pat Helland is just such a person and has written an excellent piece that collates insights and opinions from numerous thought leaders on the subject:

Since Doug [Terry] coined the phrase eventual consistency in the Bayou paper in 1995, I was interested in his perspective. When he defined eventual consistency, it meant that for each object in a collection of objects, all the replicas of each object will eventually have the same value. Then, he said: “Yeah, I should have called it eventual convergence.”

Pat Helland

This quote is significant in that many often confuse consistency as something other than convergence. For event-driven systems, we’re very interested in ensuring that services are convergent, though they may never actually be consistent since they each consume and process events at their own rate.

Helland goes on to discuss a definition by Peter Alvaro, from his 2015 PhD thesis “Data-Centric Programming for Distributed Systems”:

A system is convergent or “eventually ...