This makes me wonder how it's possible how to replicate data without being eventually consistent. I can't transmit data faster than the speed of light. It seems that the definitions here need more clarity, because eventual consistency in the broadest sense applies to everything. Is there a good example of replication consistency which isn't "eventual", but is instead immediate?

It’s all about when you acknowledge back to the client, whether you accept writes at a single writer or multiple writers, and whether reads can be served from any node. Most EC systems tend to be multi writer with async replication. This means clients get acks immediately and reads to other nodes for those values can contain various values. The speed of the network doesn’t matter from a theoretical perspective. Network speed only affects potential convergence times. Time is time regardless of the unit of measurement.

See my other comment above for distinguishing between EC and Sequential.

I don't think the OP is arguing that replicated data is not "eventually consistent" because it is as you say.

OP is arguing the blog post is trying to change the definition of "eventually consistent"... the author is saying the delay between the master and slave is not "eventually consistent"... when, exactly as you say, it is.

SQLite, appropriately configured, is trivially linearizable — everything is protected under one lock on one machine.

This explains it pretty well: https://www.cs.princeton.edu/courses/archive/spr18/cos518/do...

Here's an overly simple, impractically slow, but immediately consistent model for you: for every request from a client, ask all other nodes in the network the same query. If you get 100% consensus, return the answer, otherwise, ask again.