data.table alternative for dplyr case_when

Some time ago they introduced a nice SQL-like alternative to ifelse within dplyr, i.e. case_when.

Is there an equivalent in data.table that would allow you to specify different conditions within one [] statement, without loading additional packages?

Example:

library(dplyr)

df <- data.frame(a = c("a", "b", "a"), b = c("b", "a", "a"))

df <- df %>% mutate(
    new = case_when(
    a == "a" & b == "b" ~ "c",
    a == "b" & b == "a" ~ "d",
    TRUE ~ "e")
    )

  a b new
1 a b   c
2 b a   d
3 a a   e

It would certainly be very helpful and make code much more readable (one of the reasons why I keep using dplyr in these cases).