What is Apache Flink?
- Apache Flink, developed at Berlin TU University, Flink allow the lambda architecture and functions as a genuine streaming engine.
- It handles batch processing as a subset of streaming, especially for constrained data. Auto-adjustment is a key feature of Flink minimizing the need for extensive parameter tuning and establishing it as the first true streaming framework.
- Flink offers a streaming engine with high throughput and low latency, as well as event-time processing and state management capabilities.
- Flink applications are fault-tolerant in the case of a machine failure and use exactly-once semantics.
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.