NeurDB: An AI-powered Autonomous Data System
Beng Chin Ooi, Shaofeng Cai, Gang Chen, Yanyan Shen, Kian-Lee Tan,, Yuncheng Wu, Xiaokui Xiao, Naili Xing, Cong Yue, Lingze Zeng, Meihui Zhang,, Zhanhao Zhao

TL;DR
NeurDB is an innovative AI-powered autonomous data system that integrates AI deeply into its architecture to enable advanced in-database analytics and autonomous functionalities, aiming to revolutionize data management.
Contribution
The paper introduces NeurDB, a novel autonomous data system that fully incorporates AI into its design, advancing in-database AI analytics and system autonomy.
Findings
Conceptual and architectural overview of NeurDB
Discussion of design choices and key components
Current development status and future plans
Abstract
In the wake of rapid advancements in artificial intelligence (AI), we stand on the brink of a transformative leap in data systems. The imminent fusion of AI and DB (AIxDB) promises a new generation of data systems, which will relieve the burden on end-users across all industry sectors by featuring AI-enhanced functionalities, such as personalized and automated in-database AI-powered analytics, self-driving capabilities for improved system performance, etc. In this paper, we explore the evolution of data systems with a focus on deepening the fusion of AI and DB. We present NeurDB, an AI-powered autonomous data system designed to fully embrace AI design in each major system component and provide in-database AI-powered analytics. We outline the conceptual and architectural overview of NeurDB, discuss its design choices and key components, and report its current development and future plan.
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Taxonomy
TopicsNeural Networks and Applications
MethodsFocus
