Apache Flink
A distributed stream processing framework that handles both real-time streams and batch data with exactly-once guarantees. Used by Alibaba, Netflix, and Uber at massive scale.
What is Apache Flink?
A distributed stream processing framework that handles both real-time streams and batch data with exactly-once guarantees. Used by Alibaba, Netflix, and Uber at massive scale.
Apache Flink is a advanced concept that sits in the Stream & Batch Processing area of system design. Engineers reach for it whenever they need to reason about real-world trade-offs in that space — not just for textbook correctness, but because real production systems at companies like Netflix, Amazon, and Google make these decisions every day.
If you want to go deeper than this definition — with diagrams, code, and a quiz to lock it in — work through the "Apache Flink" lesson linked below. It walks through the why, the mechanism, the trade-offs, and how the giants actually use it in production.
Learn Apache Flink in depth
Full interactive lesson with diagrams, code examples, real-world references, and a quiz.
Open the Apache Flink lessonRelated lessons
Lessons that touch on Apache Flink as part of a larger topic.
See also
Related glossary terms you might want to look up next.
Apache Spark
A unified analytics engine for large-scale data processing with built-in modules for SQL, streaming, ML, and graph computation. Processes data in-memory for speed.
Stream Processing
Processing data continuously as it arrives, rather than in batches. Powers real-time analytics, fraud detection, and live dashboards.
Checkpointing
Periodically saving the state of a stream processing job so it can recover from failures without reprocessing everything from the beginning. Flink and Spark use distributed checkpoints.