How I Built a High-Throughput Transaction Processor with Kafka, Redis, PostgreSQL, and MongoDB

When I started building this project, I wanted to learn by building something similar to how backend systems in payment processing apps work. I wanted to build something that made me think carefully about throughput, ordering, idempotency, auditability, and failure boundaries together. That led me to build HVTP (High Volume Transaction Processor) — a portfolio-grade, event-driven transaction processor that behaves more like a small transaction backend. What made this project valuable for me wasn’t just wiring Kafka into a system. It was learning how to shape the system so the right work happened in the right place. What the project actually is At a practical level, HVTP is a signed transaction ingestion pipeline. A merchant client sends a transaction request over HTTP. The system validates the request at ingress, accepts it quickly, and then hands it off for asynchronous processing. From there, the system: validates and processes the transaction enforces idempotency persists ledger sta