Theoretical Question: Data.table vs Data.frame with Big Data
The tidyverse also encompasses readr with faster functions for reading text files, e.g. read_csv (https://cran.r-project.org/web/packages/readr/README.html).

You are confounding two issues here, speed of operations of data.table vs. data.frame, and reading in such data. 

I would venture a guess that read.csv and read.table is slow, because it does a lot of inefficient guessing and (by default) tries to convert strings to factors. When dealing with large data sets, you should always prefer to tell the routine what it is reading, rather than letting it guess. 

Lastly, if you are dealing with very large data sets, specialized subroutines that are implemented in Rcpp or the like might be preferable, assuming your data is structured.