It's not a limitation of the query tools. The problem is that users are running so many different queries against the same schema that you can't optimize for them all. Therefore, it's most important how a data warehouse performs when the optimization "tricks" don't work.
There will always be trade-offs so disagreements are to be expected. My interest is largely in what models work best for a given system, specifically Redshift. What data models have you seen in use? Are the schemas dimensionally modeled or are they flat tables?
Where have you run into limitations with dimensional modeling? Is it a lack of engineering resources on the customer side or is the approach limited in some fundamental way?
Thanks for sharing your invaluable experience. I look forward to part two!
Reasonable people can disagree on this last claim---we'll publish a v2 of this benchmark in a few months where we do more tuning https://github.com/fivetran/benchmark/issues/1