ROOT’s RNTuple and the Case for Custom Scientific Data Formats

Each month, CERN collects and stores multiple petabytes of measurement data from the Large Hadron Collider (LHC) for further analysis. These data are stored in a custom columnar format provided by CERN’s open-source software framework ROOT. However, the increased availability of general-purpose columnar data formats raises the question whether developing and maintaining a custom data format for high-energy physics (HEP) is still worth it. To address this question, we compare ROOT’s RNTuple data format against Apache ORC and Apache Parquet. We find that RNTuple stores data 6-21% more efficiently, and processes physics data 3-6x faster.

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Published
2025-09-15
DOI
https://doi.org/10.1109/escience65000.2025.00054
Primary Topic
Research Data Management Practices
Type
article
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article

ROOT’s RNTuple and the Case for Custom Scientific Data Formats

Vincenzo Eduardo Padulano, Ana-Lucia Varbanescu, Florine Willemijn de Geus, Stijn Jongbloed
Research Data Management Practices
article

ROOT’s RNTuple and the Case for Custom Scientific Data Formats

Vincenzo Eduardo Padulano, Ana-Lucia Varbanescu, Florine Willemijn de Geus, Stijn Jongbloed
article en

Abstract

Each month, CERN collects and stores multiple petabytes of measurement data from the Large Hadron Collider (LHC) for further analysis. These data are stored in a custom columnar format provided by CERN’s open-source software framework ROOT. However, the increased availability of general-purpose columnar data formats raises the question whether developing and maintaining a custom data format for high-energy physics (HEP) is still worth it. To address this question, we compare ROOT’s RNTuple data format against Apache ORC and Apache Parquet. We find that RNTuple stores data 6-21% more efficiently, and processes physics data 3-6x faster.

European Organization for Nuclear Research (CH), University of Amsterdam (NL), University of Twente (NL)
Openalex Percentile: Top 59%
Research Data Management Practices
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ROOT’s RNTuple and the Case for Custom Scientific Data Formats — Vincenzo Eduardo Padulano, Ana-Lucia Varbanescu, et al. · (2025) | TGRS Research Map | TGRS