title: What can't I do with dtplyr that I can in data.table
body: <p>Should I invest my learning effort for data wrangling in R, specifically between <code>dplyr</code>, <code>dtplyr</code> and <code>data.table</code>? </p>
  
  <ul>
  <li><p>I use <code>dplyr</code> mostly, but when the data is too big for that I will use <code>data.table</code>, which is a rare occurrence. So now that <code>dtplyr</code> v1.0 is out as an interface for <code>data.table</code>, on the surface it seems like I never need to worry about using the <code>data.table</code> interface ever again. </p></li>
  <li><p>So what are the most useful features or aspects of <code>data.table</code> that <strong>cannot</strong> be done using <code>dtplyr</code> at the moment, and that likely will never be done with <code>dtplyr</code>?</p></li>
  <li><p>On its face, <code>dplyr</code> with the benefits of <code>data.table</code> makes it sound like <code>dtplyr</code> will overtake <code>dplyr</code>. Will there be any reason to use <code>dplyr</code> once <code>dtplyr</code> has fully matured?</p></li>
  </ul>
  
  <p>Note: I am not asking about <code>dplyr</code> vs <code>data.table</code> (as in <a href="https://stackoverflow.com/questions/21435339/data-table-vs-dplyr-can-one-do-something-well-the-other-cant-or-does-poorly">data.table vs dplyr: can one do something well the other can&#39;t or does poorly?</a>), but given that one is preferred over the other for a particular problem, why wouldn't <code>dtplyr</code> be the tool to use.</p>