Real-Time Data Processing: Kafka, Flink, and the Modern Streaming Architecture

Batch processing — running data jobs nightly or hourly — was the default data architecture for a generation. But in an era where customers expect real-time personalisation, fraud detection must happen in milliseconds, and operational dashboards must reflect current reality, batch is no longer fit for purpose.

Why Kafka Won

Apache Kafka has become the de facto standard for real-time data streaming because of its durability (it persists all messages to disk), high throughput (millions of messages per second), and replay capability (consumers can reprocess historical events).