Practical Event-Driven Microservices: A Database-Centric Alternative to Message Brokers An Architectural Framework for Moderate-Scale Systems

Modern distributed systems often rely on message brokers such as Apache Kafka or RabbitMQ to achieve reliable event-driven communication. While effective, these systems introduce considerable operational complexity and cost, especially for teams operating below large-scale throughput requirements. This paper presents a database-centric alternative to broker-based architectures that preserves the key benefits of microservices—service isolation, independent deployment, and horizontal scalability—without the accompanying infrastructure burden, specifically targeting asynchronous workflows tolerating multi-second latency. We introduce a multi-pipeline outbox pattern that extends the traditional transactional outbox with domain-specific constraints and separation of concerns. Through architectural analysis and theoretical modeling based on published PostgreSQL benchmarks, we show that this approach reduces operational complexity by approximately fivefold compared to Kafka-based systems while maintaining sufficient throughput for moderate-scale workloads (1,000--5,000 events/second on single-database deployments). We provide a quantitative decision framework to guide architecture selection based on throughput requirements, latency tolerance, team size, and operational maturity. For distributed systems operating asynchronously at moderate scale, our analysis demonstrates that database-centric event processing provides an optimal balance between scalability, simplicity, and reliability. However, this architecture is not universal—latency-sensitive synchronous workflows, multi-region deployments, and sustained throughput exceeding 5,000 events per second warrant Kafka adoption.