This changes only affect a small percentage of users that need to run single Redis instances with datasets that are larger than the computer memory.
Our default back end is to run as an in memory DB, and most of the design and goals are related to this mode. But I think that most of the value of Redis is its data model, and I bet it will survive Redis itself, so the idea is, let's look to alternatives that make this data model working well with data sets bigger than RAM.
Our old solution was VM, but we found it is not ideal, does not work well with the Redis in-memory back end persistence ideas (that are instead working well without VM). What to do then? Keep trying with the wrong solution? :) I guess not, open source also means that if the cure for a disease is not good enough we put things into the trash and try again and again, as the sole goal should be the progress of the technology we are trying to put in the hand of users.
So we have a new model now, and will test how it works in practice. What we said is: for write heavy applications where performances matter, use Redis as an in-memory DB. It works well, it's well tested, and we can count many happy users.
But if the Redis data model solves your problems, and you have a read-heavy application with tons of data, we are going to provide an alternative that could work well.