[EN] Data analysis workflows in High Energy Physics (HEP) read data written in the ROOT columnar format. Such data has traditionally been stored in files that are often read via the network from remote storage facilities, which represents a performance penalty especially for data processing workflows that are I/O bound. To address that issue, this paper presents a new caching mechanism, implemented in the I/O subsystem of ROOT, which is independent of the storage backend used to write the dataset. Notably, it can be used to leverage the speed of high-bandwidth, low-latency object stores. The performance of this caching approach is evaluated by running a real physics analysis on an Intel DAOS cluster, both on a single node and distributed on multiple nodes., This work benefited from the support of the CERN Strategic R&D Programme on Technologies for Future Experiments [1] and from grant PID2020-113656RB-C22 funded by Ministerio de Ciencia e Innovacion MCIN/AEI/10.13039/501100011033. The hardware used to perform the experimental evaluation involving DAOS (HPE Delphi cluster described in Sect. 5.2) was made available thanks to a collaboration agreement with Hewlett-Packard Enterprise (HPE) and Intel. User access to the Virgo cluster at the GSI institute was given for the purpose of running the benchmarks using the Lustre filesystem.