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Learn more →Enterprise-grade data streaming platform for real-time financial processing

This enterprise-grade solution handles real-time financial data processing with sub-second latency, ensuring compliance with banking regulations while maintaining 99.99% uptime.
The bank needed to migrate from a legacy ETL-based data processing model to a real-time streaming infrastructure. The existing ETL system was too slow, too rigid, and not designed for real-time processing. The new platform had to:
In short: a real-time streaming architecture that combines banking standards with startup speed.
We developed a fully event-driven backend platform based on Apache Kafka as the central messaging backbone.
All services were containerized and orchestrated in a Kubernetes cluster:
To prevent data loss and duplicates with millions of events, we implemented:
Monitoring, logging, and alerting are based on:
This gives the bank team real-time insight into latencies, throughput, and system health.
Backend: Java 17 · Spring
Streaming: Apache Kafka
Database: PostgreSQL
Infrastructure: Docker · Kubernetes
Duration: 9 months
Team: 5 engineers
The same streaming-first principles and microservice orchestration logic are now core to H-Studio's backend designs for modern startups — where live analytics, event logs, and real-time customer data are essential.
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