The gap between events happening and insights being available is a competitive disadvantage. Modern enterprises need real-time data architectures.
Streaming vs. Batch
Batch: Process data in large chunks on a schedule. Simple but introduces latency.
Streaming: Process data as it arrives. Complex but enables real-time insights.
Most organizations need both: the Lambda or Kappa architecture.
Key Technologies
**Apache Kafka**: The backbone of most streaming architectures. Handles millions of events per second.
**Apache Flink**: Real-time processing with exactly-once semantics.
**ksqlDB**: SQL interface for streaming data.
Design Patterns
- . Event sourcing for audit trails
- . CQRS for read/write optimization
- . Materialized views for query performance
The investment in real-time architectures pays off in operational efficiency and competitive advantage.