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Challenges & Opportunities in Automating DBMS: A Qualitative Study

Year: 2024

Type: conference-paper

Abstract: Background. In recent years, the volume and complexity of data handled by Database Management Systems (DBMS) have surged, necessitating greater efforts and resources for efficient administration. In response, numerous automation tools for DBMS administration have emerged, particularly with the progression of AI and machine learning technologies. However, despite these advancements, the industry-wide adoption of such tools remains limited.

Source: IEEE/ACM International Conference on Automated Software Engineering (ASE)

DOI: 10.1145/3691620.3695264

Authors: Yifan Wang, Pierre Bourhis, Romain Rouvoy, Patrick Royer

Institutions: Institut national de recherche en sciences et technologies du numérique, Université de Lille, Centre de Recherche en Informatique, Signal et Automatique de Lille, Centre National de la Recherche Scientifique, Orange (France)

Language: English

Topic: Advanced Database Systems and Queries

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4403536773

FWCI: 0.911

Cites: 25

Cited by: 2

Related to: 10