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<p>Conventional databases support either retroactive or proactive changes, but not both simultaneously, resulting in the loss of valuable historical data. Bitemporal databases resolve this problem by supporting two temporal dimensions simultaneously: valid time and transaction time. This approach enhances data integrity and traceability in real-world applications. Although numerous studies have examined bitemporal databases, a comprehensive review of the field is still lacking. Therefore, we conducted a hybrid systematic literature review following the PRISMA framework, supplemented by bibliometric and scientometric analyses, covering publications from January 1995 to January 2026. Four main databases were chosen: IEEE, Scopus, ProQuest, and Web of Science. Subsequently, 54 papers were analysed, providing unique insights into bitemporal data modelling, querying, and applications. Key gaps identified include the need for hybrid Data Base Management System (DBMS) infrastructures, limited empirical validation on industrial-scale datasets, insufficient cloud-native temporal optimisation strategies, and underdeveloped integration of bitemporal data structures with AI-driven predictive analytics. Finally, this study summarises current progress in bitemporal database research, highlights key implementation challenges, and emphasises its strong potential to improve data accuracy, traceability, and temporal consistency across diverse application areas.</p>

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Comprehensive insights into bitemporal databases: a PRISMA-guided systematic literature review

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月11日

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  • Gokul Neelamegam,
  • Jagdev Bhogal,
  • Parnia Samimi,
  • Omer Ozturkoglu

摘要

Conventional databases support either retroactive or proactive changes, but not both simultaneously, resulting in the loss of valuable historical data. Bitemporal databases resolve this problem by supporting two temporal dimensions simultaneously: valid time and transaction time. This approach enhances data integrity and traceability in real-world applications. Although numerous studies have examined bitemporal databases, a comprehensive review of the field is still lacking. Therefore, we conducted a hybrid systematic literature review following the PRISMA framework, supplemented by bibliometric and scientometric analyses, covering publications from January 1995 to January 2026. Four main databases were chosen: IEEE, Scopus, ProQuest, and Web of Science. Subsequently, 54 papers were analysed, providing unique insights into bitemporal data modelling, querying, and applications. Key gaps identified include the need for hybrid Data Base Management System (DBMS) infrastructures, limited empirical validation on industrial-scale datasets, insufficient cloud-native temporal optimisation strategies, and underdeveloped integration of bitemporal data structures with AI-driven predictive analytics. Finally, this study summarises current progress in bitemporal database research, highlights key implementation challenges, and emphasises its strong potential to improve data accuracy, traceability, and temporal consistency across diverse application areas.