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Published on in Vol 14 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/82924, first published .
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Benchmarking Fast Healthcare Interoperability Resources–Based Analytics: Quantitative Study of RESTful Server Queries and Big Data Engines

Benchmarking Fast Healthcare Interoperability Resources–Based Analytics: Quantitative Study of RESTful Server Queries and Big Data Engines

Christian Gulden   1, 2 , Dr ;   Marvin Kampf   3 , MSc ;   Detlef Kraska   3 , Dr ;   John Grimes   4 , BIT ;   Thomas Ganslandt   1, 2, 3 , Prof Dr ;   Hans-Ulrich Prokosch   1, 2, 3 , Prof Dr ;   Susanne A. Seuchter   3 , BSc ;   Jonathan M. Mang   3 , Dr ;   Peter Pallaoro   2, 5, 6 , MSc ;   Paul-Christian Volkmer   7 , MSc ;   Jasmin Ziegler   2, 3 , MSc

1 Lehrstuhl für Medizinische Informatik, Institut für Medizininformatik, Biometrie und Epidemiologie, Friedrich-Alexander-Universität-Erlangen-Nürnberg, Erlangen, Germany

2 Bavarian Cancer Research Center (BZKF), Erlangen, Germany

3 Medical Center for Information and Communication Technology, Universitätsklinikum Erlangen, Erlangen, Germany

4 CSIRO Health and Biosecurity, Australian e-Health Research Centre, Brisbane, Australia

5 Chair of Medical Informatics, Institute for AI and Informatics in Medicine (AIIM), TUM University Hospital, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany

6 Data Integration Center, TUM University Hospital, TUM School of Medicine and Health, Technical University of Munich, Munich, Germany

7 Anneliese Pohl Krebszentrum Marburg, Comprehensive Cancer Center, Universitätsklinikum Gießen und Marburg, Marburg, Germany

Corresponding Author:

  • Christian Gulden, Dr
  • Lehrstuhl für Medizinische Informatik
  • Institut für Medizininformatik, Biometrie und Epidemiologie
  • Friedrich-Alexander-Universität-Erlangen-Nürnberg
  • Wetterkreuz 15
  • Erlangen
  • Germany
  • Phone: 49 9131 85 677
  • Email: christian.gulden@fau.de