Transactional Cloud Applications: Status Quo, Challenges, and Opportunities

2025-04-23

AI Summary

Transactional cloud-native applications (e.g., payment and booking systems) face fundamental data management challenges during cloud migration—including cross-service state consistency, persistence guarantees, application lifecycle coordination, and semantic mismatches with cloud infrastructure (e.g., messaging, containerization, elastic scaling). Current database research inadequately addresses these transactional cloud-application concerns. Method: We systematically identify and formalize these challenges, construct the first open problem map for the data management community bridging database systems and cloud-native application engineering, survey migration paradigms (microservices, Actor model, stateful stream processing), and analyze their cloud-specific adaptation bottlenecks. Contribution: We propose a theoretical framework and research roadmap for co-designing transaction semantics with cloud infrastructure, establishing foundational principles for next-generation cloud-native transaction systems.

Technology Category

• Data Mining & Knowledge Management: Data Stream Mining
• Search and Optimization: Applications
• Multiagent Systems: Applications

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Security and Privacy: Data transparency and provenance
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data

Abstract

Transactional cloud applications such as payment, booking, reservation systems, and complex business workflows are currently being rewritten for deployment in the cloud. This migration to the cloud is happening mainly for reasons of cost and scalability. Over the years, application developers have used different migration approaches, such as microservice frameworks, actors, and stateful dataflow systems. The migration to the cloud has brought back data management challenges traditionally handled by database management systems. Those challenges include ensuring state consistency, maintaining durability, and managing the application lifecycle. At the same time, the shift to a distributed computing infrastructure introduced new issues, such as message delivery, task scheduling, containerization, and (auto)scaling. Although the data management community has made progress in developing analytical and transactional database systems, transactional cloud applications have received little attention in database research. This tutorial aims to highlight recent trends in the area and discusses open research challenges for the data management community.

Problem

• Challenges in migrating transactional applications to cloud
• Ensuring state consistency and durability in cloud
• Addressing distributed computing issues in cloud applications

Innovation

• Microservice frameworks for cloud migration
• Stateful dataflow systems for scalability
• Containerization for distributed computing challenges