Intelligent Data Migration Approaches: Investigating the Opportunities and Challenges in Transitioning Relational Databases to Big Data Frameworks for Autonomous Vehicle Applications

Abstract

The rapid evolution of autonomous vehicle (AV) technologies demands sophisticated data management strategies to handle the enormous volumes of data generated. Traditional relational databases, while reliable, are often inadequate for managing the complexity and scale of data required for AV systems. This paper explores the intelligent approaches to data migration, focusing on transitioning from relational databases to big data frameworks that can better support AV applications. The study delves into the potential opportunities these frameworks offer, such as enhanced data processing capabilities, scalability, and improved data analytics, while also addressing the significant challenges, including data integrity, compatibility issues, and the complexity of migration processes. Through an examination of current methodologies and technological advancements, the paper provides insights into the best practices for facilitating this transition, ensuring that the migration process enhances the overall efficiency and performance of AV systems.