Persistence and Big Data Analytics Architectures for Smart Connected Vehicles

TL;DR

This paper discusses the evolution of data persistence architectures for smart connected vehicles, highlighting the transition from relational databases to NoSQL and hybrid solutions to meet scalability and availability needs.

Contribution

It introduces TYPHON, a hybrid data persistence architecture that balances relational and NoSQL database advantages for smart vehicle data management.

Findings

TYPHON supports scalable and highly available data storage.

Hybrid architecture reduces inconsistency and improves fault tolerance.

Facilitates migration from relational to NoSQL databases.

Abstract

Up until recently, relational databases were considered as the de-facto technology for persisting and managing large volumes of data. This came to change with the emergence of enterprises producing extremely large datasets and having unprecedentedly high availability requirements. The need for levels of availability beyond those supported by relational databases and the challenges involved in scaling such databases horizontally led to the emergence of a new generation of purpose-specific databases grouped under the term NoSQL. The NoSQL databases despite being designed with horizontal scalability as a primary concern and deliver increased availability and fault-tolerance, they have the cost of temporary inconsistency and reduced durability of data. The present paper presents a concept and application of how TYPHON aims to face the challenges emerging from the attempts to balance the best world of relational and NoSQL databases, by supporting the migration towards hybrid data persistence architectures.