1 year ago

Streaming data has become a must-have as organizations seek real-time insights to better serve customers, optimize operational efficiency and combat fraud. Platforms like Apache Kafka solve some of the problems associated with streaming data from many origin points to one or more destinations.

In cases like these, your stack needs both data streaming and stream processing, and that’s where Apache Flink is invaluable.

Here are three key reasons why Flink is such a valuable complement to Kafka for applications that require stream processing.

For unbounded data streams, Apache Flink provides state and context, such as time windows, making nonstop processing of those streams in real time possible.