  Over the last two decades, ROOT TTree has been used for storing over one
exabyte of High-Energy Physics (HEP) events. The TTree columnar on-disk layout
has been proved to be ideal for analyses of HEP data that typically require
access to many events, but only a subset of the information stored for each of
them. Future colliders, and particularly HL-LHC, will bring an increase of at
least one order of magnitude in the volume of generated data. Therefore, the
use of modern storage hardware, such as low-latency high-bandwidth NVMe devices
and distributed object stores, becomes more important. However, TTree was not
designed to optimally exploit modern hardware and may become a bottleneck for
data retrieval. The ROOT RNTuple I/O system aims at overcoming TTree's
limitations and at providing improved efficiency for modern storage systems. In
this paper, we extend RNTuple with a backend that uses Intel DAOS as the
underlying storage, demonstrating that the RNTuple architecture can accommodate
high-performance object stores. From the user perspective, data can be accessed
with minimal changes to the code, that is by replacing a filesystem path by a
DAOS URI. Our performance evaluation shows that the new backend can be used for
realistic analyses, while outperforming the compatibility solution provided by
the DAOS project.
