Data & Infrastructure

Streaming Architecture

A streaming architecture processes data continuously in real time as it is created — unlike batch processing, which handles data periodically in batches. It uses event streams and message brokers to enable data flows between systems with minimal latency, and is the foundation for real-time dashboards, IoT processing, and reactive AI systems.

Why does this matter?

For companies with time-critical processes, streaming is essential: machine monitoring in production, real-time fraud detection in payments, or immediate inventory updates on online orders. Streaming architectures transform your business from reactive to proactive — problems are detected before they escalate.

How IJONIS uses this

We deploy Apache Kafka as the central event backbone, complemented by Apache Flink or Kafka Streams for complex real-time processing. For mid-sized businesses, we size the architecture appropriately — from small, focused streaming solutions to enterprise-wide event-driven architectures. Managed services like Confluent Cloud reduce operational complexity.

Frequently Asked Questions

Does my company really need real-time data processing?
Not every process needs real time. We analyze your requirements and recommend streaming only where latency is business-critical. Often a combination suffices: streaming for time-critical processes (orders, alerts) and batch for analytical evaluations (reports, ML training).
What does a streaming architecture cost to operate?
Costs depend on data volume and processing complexity. Managed services like Confluent Cloud start at EUR 200-500/month for typical mid-market scenarios. Self-hosted Kafka requires more expertise but offers lower costs at high volumes. We size according to your needs.

Want to learn more?

Find out how we apply this technology for your business.