Temporal Data Management—An Overview

Michael Hanspeter Böhlen, Anton Dignös, Johann Gamper, Christian Søndergaard Jensen

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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Abstract

Despite the ubiquity of temporal data and considerable research on the effective and efficient processing of such data, database systems largely remain designed for processing the current state of some modeled reality. More recently, we have seen an increasing interest in the processing of temporal data that captures multiple states of reality. The SQL:2011 standard incorporates some temporal support, and commercial DBMSs have started to offer temporal functionality in a step-by-step manner, such as the representation of temporal intervals, temporal primary and foreign keys, and the support for so-called time-travel queries that enable access to past states.

This tutorial gives an overview of state-of-the-art research results and technologies for storing, managing, and processing temporal data in relational database management systems. Following an introduction that offers a historical perspective, we provide an overview of basic temporal database concepts. Then we survey the state-of-the-art in temporal database research, followed by a coverage of the support for temporal data in the current SQL standard and the extent to which the temporal aspects of the standard are supported by existing systems. The tutorial ends by covering a recently proposed framework that provides comprehensive support for processing temporal data and that has been implemented in PostgreSQL.
Original languageEnglish
Title of host publicationBusiness Intelligence and Big Data - 7th European Summer School, eBISS 2017, Tutorial Lectures
EditorsEsteban Zimanyi
Number of pages33
Volume324
PublisherSpringer
Publication date1 Jan 2018
Pages51-83
ISBN (Print)978-3-319-96654-0
ISBN (Electronic)978-3-319-96655-7
DOIs
Publication statusPublished - 1 Jan 2018
EventEuropean Business Intelligence and Big Data Summer School -
Duration: 2 Jul 20177 Jul 2017

Conference

ConferenceEuropean Business Intelligence and Big Data Summer School
Period02/07/201707/07/2017
SeriesLecture Notes in Business Information Processing
ISSN1865-1348

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Böhlen, M. H., Dignös, A., Gamper, J., & Jensen, C. S. (2018). Temporal Data Management—An Overview. In E. Zimanyi (Ed.), Business Intelligence and Big Data - 7th European Summer School, eBISS 2017, Tutorial Lectures (Vol. 324, pp. 51-83). Springer. Lecture Notes in Business Information Processing https://doi.org/10.1007/978-3-319-96655-7_3
Böhlen, Michael Hanspeter ; Dignös, Anton ; Gamper, Johann ; Jensen, Christian Søndergaard. / Temporal Data Management—An Overview. Business Intelligence and Big Data - 7th European Summer School, eBISS 2017, Tutorial Lectures. editor / Esteban Zimanyi. Vol. 324 Springer, 2018. pp. 51-83 (Lecture Notes in Business Information Processing).
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Böhlen, MH, Dignös, A, Gamper, J & Jensen, CS 2018, Temporal Data Management—An Overview. in E Zimanyi (ed.), Business Intelligence and Big Data - 7th European Summer School, eBISS 2017, Tutorial Lectures. vol. 324, Springer, Lecture Notes in Business Information Processing, pp. 51-83, European Business Intelligence and Big Data Summer School, 02/07/2017. https://doi.org/10.1007/978-3-319-96655-7_3

Temporal Data Management—An Overview. / Böhlen, Michael Hanspeter; Dignös, Anton; Gamper, Johann; Jensen, Christian Søndergaard.

Business Intelligence and Big Data - 7th European Summer School, eBISS 2017, Tutorial Lectures. ed. / Esteban Zimanyi. Vol. 324 Springer, 2018. p. 51-83 (Lecture Notes in Business Information Processing).

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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Böhlen MH, Dignös A, Gamper J, Jensen CS. Temporal Data Management—An Overview. In Zimanyi E, editor, Business Intelligence and Big Data - 7th European Summer School, eBISS 2017, Tutorial Lectures. Vol. 324. Springer. 2018. p. 51-83. (Lecture Notes in Business Information Processing). https://doi.org/10.1007/978-3-319-96655-7_3