I personally think that the tidyverse ecosystem really makes a huge difference to my daily work. It is so easy to use and has a complete set of tools suitable for most of my tasks. What's better, dplyr package can easily work with database like Postgresql and Spark, which partially solve the memory constraint issue of R. However, tidyverse is not that great when it comes to performance. To my own experience, when I use dplyr with broom, the performance gets even worse.
I started R with learning data.table, but since I came across tidyverse, I don't use data.table that frequently. I turn to data.table when dplyr is too slow.
I was wondering if there is any work being done to integrate the strength of dplyr and data.table to solve the memory constraint and performance issues in a unified framework.