  Distinct HEP workflows have distinct I/O needs; while ROOT I/O excels at
serializing complex C++ objects common to reconstruction, analysis workflows
typically have simpler objects and can sustain higher event rates. To meet
these workflows, we have developed a "bulk I/O" interface, allowing multiple
events data to be returned per library call. This reduces ROOT-related
overheads and increases event rates - orders-of-magnitude improvements are
shown in microbenchmarks. Unfortunately, this bulk interface is difficult to
use as it requires users to identify when it is applicable and they still
"think" in terms of events, not arrays of data. We have integrated the bulk I/O
interface into the new RDataFrame analysis framework inside ROOT. As
RDataFrame's interface can provide improved type information, the framework
itself can determine what data is readable via the bulk IO and automatically
switch between interfaces. We demonstrate how this can improve event rates when
reading analysis data formats, such as CMS's NanoAOD.
