Apache Flink

Apache Flink is a distributed processing engine for stateful stream processing and batch analytics. It is designed for low-latency, high-throughput pipelines with strong consistency, fault tolerance, and event-time processing.

Key Features

• Stateful stream processing with exactly-once consistency (depending on connector and sink support)
• Event-time semantics with watermarks and advanced windowing
• Fault tolerance via checkpoints and savepoints for upgrades, rollbacks, and migrations
• Unified runtime for streaming and batch workloads
• Rich APIs including DataStream and Table/SQL for declarative processing
• Scalable parallel execution on clusters with fine-grained state management

Use Cases

• Real-time analytics and monitoring pipelines over logs and events
• Stream ETL and enrichment between messaging systems and databases
• Stateful event-driven applications such as fraud detection or alerting

Limitations and Considerations

• Operating Flink reliably requires careful tuning of state backends, checkpoints, and connector configuration
• Some delivery guarantees depend on the chosen connectors and sinks, not only the core engine

Apache Flink is well-suited for teams building reliable, stateful real-time systems and unified streaming/batch data pipelines. It provides robust primitives for event-time processing and recovery, while scaling from small deployments to large cluster environments.