Flink supports both batch and streaming processes. Apache Flink is an excellent choice for various use cases, some of which are:-

In event-driven applications, data and computation are co-located. Because to its nature, flink is naturally fit to process such applications.

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Since flink can process both batch and streaming data so it is very useful to create real-time dashboards.

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Flink provides many connectors such as Kafka, JDBC, etc. which help to create a real-time data pipeline.

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IoT applications can take the real-time processing capability of flink to develop many IoT applications like connected cars, or smart applications.

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Since flink provides very less latency, the banking and cybersecurity team can use flink to delete fraud in real-time.

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Flink supports both batch and streaming processes. Apache Flink is an excellent choice for various use cases, some of which are:-

In event-driven applications, data and computation are co-located. Because to its nature, flink is naturally fit to process such applications.

1. Event-driven application

Since flink can process both batch and streaming data so it is very useful to create real-time dashboards.

2. Data Analytics Applications

Flink provides many connectors such as Kafka, JDBC, etc. which help to create a real-time data pipeline.

3. Data Pipeline Applications

IoT applications can take the real-time processing capability of flink to develop many IoT applications like connected cars, or smart applications.

4. IOT applications

Since flink provides very less latency, the banking and cybersecurity team can use flink to delete fraud in real-time.

5. Fraud detection

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