Real-time data processing has become essential for modern businesses. This guide explores best practices for building scalable, low-latency data pipelines.
Stream Processing Architecture
The foundation of real-time processing is a robust streaming architecture. Key components include:
- Message brokers (Kafka, Kinesis)
- Stream processors (Flink, Spark Streaming)
- Time-series databases
- Real-time analytics engines
Performance Optimization
Achieving sub-millisecond latency requires careful optimization at every layer of your stack.