Apache Flink
What it is: Distributed stream processing framework. True real-time (not micro-batching). Stateful event-driven applications with exactly-once guarantees.
What It Does Best
True streaming. Processes events as they arrive. No micro-batching delays. Sub-second latency at scale.
Stateful processing. Maintain state across billions of events. Exactly-once semantics even with failures.
Event time processing. Handle out-of-order events correctly. Watermarks, late data, complex time windows.
Pricing
Free: Open source, Apache 2.0. Managed Flink: AWS Kinesis Data Analytics, Confluent Cloud, Alibaba Cloud.
When to Use It
✅ Real-time event processing pipelines
✅ Complex event pattern detection
✅ Stateful stream transformations
✅ Continuous ETL and data enrichment
When NOT to Use It
❌ Batch processing (use Spark)
❌ Simple streaming (Kafka Streams simpler)
❌ Small team without stream expertise
Bottom line: Most advanced stream processing framework. More complex than Spark Streaming but truly real-time. Choose Flink for mission-critical streaming where latency matters. Steep learning curve, powerful results.