en/docs/apache-flink

Apache Flink is an open-source stream processing framework for real-time data processing. It is designed to run in all common cluster environments, perform computations at in-memory speed, and at any scale. Here are some key features of Apache Flink:

Key Features

• Stream Processing: Flink is designed for processing unbounded and bounded data streams.
• Fault Tolerance: Flink provides exactly-once state consistency semantics.
• Scalability: It can scale to thousands of nodes.
• Event Time Processing: Flink supports event time processing and watermarks.
• High Throughput and Low Latency: Flink achieves high throughput and low latency through its architecture.

Use Cases

• Real-time Analytics: Perform real-time analytics on streaming data.
• Fraud Detection: Detect fraudulent activities in real-time.
• Streaming ETL: Perform ETL operations on streaming data.
• Machine Learning: Build real-time machine learning applications.

Getting Started

To get started with Apache Flink, you can download the latest release from the Apache Flink website.

Resources

• Apache Flink Documentation
• Apache Flink Community

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Apache Flink Architecture