Optimizing event-driven architectures for real-time financial transactions: A comparative study of streaming technologies

Abstract

This article compares event-driven architectures for real-time financial transactions, examining leading streaming technologies through the lens of financial industry requirements. The transition from batch processing to real-time event processing has been driven by customer expectations, regulatory mandates, and competitive pressures in modern financial services. Through evaluation of architectural patterns including event sourcing, CQRS, and saga patterns, the article demonstrates how different streaming technologies address immutability, consistency, and performance challenges unique to financial contexts. Performance characteristics and security considerations are assessed across platforms, providing decision frameworks for financial institutions balancing throughput, latency, and compliance requirements. Additionally, the article explores emerging technological trends that promise to further transform financial processing capabilities, including serverless computing, multi-cloud strategies, artificial intelligence integration, distributed ledger technologies, and edge computing solutions.