Modern Temporal Data Models: Strengths and Weaknesses

Petković, Dušan

doi:10.1007/978-3-319-18422-7_12

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…Since the introduction of the temporal features in the SQL:2011 standard [58,97], major database vendors have started to implement temporal support in their database management systems [59,73,74]. Some companies realized the need for supporting temporal data earlier, and they extended their database systems with basic temporal features, such as data types, functions, and time travel queries, that make past states of a database available for querying.…”

Section: Temporal Data Support In Commercial Dbmssmentioning

confidence: 99%

Temporal Data Management – An Overview

Böhlen

Dignös

Gamper

et al. 2018

Lecture Notes in Business Information Processing

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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.

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Section: Temporal Data Support In Commercial Dbmssmentioning

confidence: 99%

Temporal Data Management – An Overview

Böhlen

Dignös

Gamper

et al. 2018

Lecture Notes in Business Information Processing

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show abstract

“…Temporal support in relational database systems has gained significant interest during the last years, witnessed by temporal features in the SQL:2011 standard [5,28,32] as well as by the numerous database products that offer selected temporal features, such as IBM DB2 [36], Oracle [31], Teradata [1], Microsoft SQL Server [30], and PostgreSQL [35].…”

Section: Introductionmentioning

confidence: 99%

Leveraging range joins for the computation of overlap joins

et al. 2021

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Joins are essential and potentially expensive operations in database management systems. When data is associated with time periods, joins commonly include predicates that require pairs of argument tuples to overlap in order to qualify for the result. Our goal is to enable built-in systems support for such joins. In particular, we present an approach where overlap joins are formulated as unions of range joins, which are more general purpose joins compared to overlap joins, i.e., are useful in their own right, and are supported well by B+-trees. The approach is sufficiently flexible that it also supports joins with additional equality predicates, as well as open, closed, and half-open time periods over discrete and continuous domains, thus offering both generality and simplicity, which is important in a system setting. We provide both a stand-alone solution that performs on par with the state-of-the-art and a DBMS embedded solution that is able to exploit standard indexing and clearly outperforms existing DBMS solutions that depend on specialized indexing techniques. We offer both analytical and empirical evaluations of the proposals. The empirical study includes comparisons with pertinent existing proposals and offers detailed insight into the performance characteristics of the proposals.

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“…Furthermore, there is no temporal query language, like TSQL2 (Snodgrass et al , 1995), or conventional query language with temporal facilities, like SQL:2011 (Kulkarni and Michels, 2012), that supports detecting and/or repairing data inconsistencies resulting from retroactive updates (Etzion et al , 1994). Moreover, although some mainstream commercial DBMSs, including Oracle, IBM DB2, Teradata and MS SQL Server, provide temporal functionalities, as surveyed in (Grandi, 2015; Künzner and Petkovic, 2015; Petkovic, 2015; Petkovic, 2016), none of them supports the management of the effects of retroactive updates on the database consistency. Notice here that, to the best of our knowledge, current ERPs (Monk and Wagner, 2013), including SAP ERP, Oracle ERP, Microsoft Dynamics, Sage Business Solutions, Infor and Epicor, do not allow the management of time-varying data.…”

Section: Introductionmentioning

confidence: 99%

Deferred repair of inconsistencies resulting from retroactive updates of temporal XML currency data

Hamrouni

Grandi

Brahmia

2017

IJWIS

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Purpose A temporal XML database could become an inconsistent model of the represented reality after a retroactive update. Such an inconsistency state must be repaired by performing corrective actions (e.g. payment of arrears after a retroactive salary increase) either immediately (i.e. at inconsistency detection time) or in a deferred manner, at one or several chosen repair times according to application requirements. The purpose of this work is to deal with deferred and multi-step repair of detected data inconsistencies. Design/methodology/approach A general approach for deferred and stepwise repair of inconsistencies that result from retroactive updates of currency data (e.g. the salary of an employee) in a valid-time or bitemporal XML database is proposed. The approach separates the inconsistency repairs from the inconsistency detection phase and deals with the execution of corrective actions, which also take into account enterprise’s business rules that define some relationships between data. Findings Algorithms, methods and support data structures for deferred and multi-step inconsistency repair of currency data are presented. The feasibility of the approach has been shown through the development and testing of a system prototype, named Deferred-Repair Manager. Originality/value The proposed approach implements a new general and flexible strategy for repairing detected inconsistencies in a deferred manner and possibly in multiple steps, according to varying user’s requirements and to specifications which are customary in the real world.

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Modern Temporal Data Models: Strengths and Weaknesses

Cited by 4 publications

References 9 publications

Temporal Data Management – An Overview

Temporal Data Management – An Overview

Leveraging range joins for the computation of overlap joins

Deferred repair of inconsistencies resulting from retroactive updates of temporal XML currency data

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