I like Pearl's work a lot more than his opinions on who invented what, and who is right about what. For that reason, I would wholeheartedly recommend his books but I would also recommend skipping any sideshows about related literature.
Fact is, Pearl selectively picks literature concerned with causality and, in particular, literature not successfully tackling the subject.
He does ignore many other approaches to the issue, especially parallel developments to tackle problems in fields that he specifically critiques. In other words: Pearl, next to being a great researcher, is also a showman who knows how to build a following.
The essence of the debate is this: Neither Pearl's framework, nor anyone else's capture all valid approaches to causal inference. One can construct cases in Rubin's framework that DAG can not solve and vice-versa. The downside to Pearl's approach is that it is - right now - more difficult to implement. The cases where DAG undoubtedly succeeds better than other approaches are, in a sense, unlikely to succeed as a practical research projects.
That being said, a great strength of such graphical models is that they allow quite sophisticated reasoning in several well-known simple but non-intuitive cases. Such reasoning otherwise requires an immense amount of experience and / or education on the pitfalls of causal inference. That is also a reason why I would like to see this framework taught more in schools.
All in all, as another great post in this thread has pointed out, much of the debate is in violent agreement on base issues. Once this issue transcends the egos involved, much progress will be made and that is, in my view, very exciting.