Historical Graphs: Models, Storage, Processing

Pitoura, Evaggelia

doi:10.1007/978-3-319-96655-7_4

Cited by 3 publications

(1 citation statement)

References 27 publications

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“…Real graphs, however, are dynamic [12] such that their topology is subject to continuous changes. In this context, a new emphasis is being placed to support time as a first class citizen in graph management systems [13,14,15,16]. Most of these systems rely on real-world temporal graphs to evaluate their proposed methods.…”

Section: Introductionmentioning

confidence: 99%

RTGEN++: A Relative Temporal Graph GENerator

Massri

Miklós

Raipin

et al. 2023

Future Generation Computer Systems

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Section: Introductionmentioning

confidence: 99%

RTGEN++: A Relative Temporal Graph GENerator

Massri

Miklós

Raipin

et al. 2023

Future Generation Computer Systems

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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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Historical Graph Management in Dynamic Environments

et al. 2020

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Since dynamic graph data continuously change over time, it is necessary to manage historical data for accessing a snapshot graph at a specific time. In this paper, we propose a new historical graph management scheme that consists of an intersection snapshot and a delta snapshot to enhance storage utilization and historical graph accessibility. The proposed scheme constantly detects graph changes and calculates a common subgraph ratio between historical graphs over time. If the common subgraph ratio is lower than a threshold value, the intersection snapshot stores the common subgraphs within a time interval. A delta snapshot stores the subgraphs that are not contained in the intersection snapshot. Several delta snapshots are connected to the intersection snapshot to maintain the modified subgraph over time. The efficiency of storage space is improved by managing common subgraphs stored in the intersection snapshot. Furthermore, the intersection and delta snapshots can be connected to search a graph at a specific time. We show the superiority of the proposed scheme through various performance evaluations.

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Historical Graphs: Models, Storage, Processing

Cited by 3 publications

References 27 publications

RTGEN++: A Relative Temporal Graph GENerator

RTGEN++: A Relative Temporal Graph GENerator

Temporal Data Management – An Overview

Historical Graph Management in Dynamic Environments

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