Apache Kafka and Flink
How does Kafka and Flink work together?
Flink’s Kafka connectors provide some metrics through Flink’s metrics system to check the connector behavior.
When to use Kafka and when to use Flink?
Kafka Streams follows a messaging approach and Flink uses a dataflow model. Kafka Streams is generally considered easier to learn and use than Flink. However, Flink has advanced features and is suitable for a wider range of applications.
Does Flink commit offsets to Kafka?
If checkpointing is enabled, the Flink Kafka Consumer will commit the offsets saved in checkpointed states after the checkpoints are completed.
Is Flink a message broker?
Flink is the most used computational framework for performing complex event processing and analytics on streaming data.
Apache Kafka vs Flink
Apache Kafka and Apache Flink are two powerful tools in big data and stream processing. While Kafka is known for its robust messaging system, Flink is good in real-time stream processing and analytics. Understanding the differences between these two tools is important for choosing the right one for our use case.
In this article, we’ll explore the key features, advantages, and disadvantages of Apache Kafka and Apache Flink and compare them in a tabular format to highlight their differences.
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