Apache Flink is an open source framework for stateful computations over streams of data. By design, Flink also support batch processing. Large amounts of data from various sources such as databases, file systems or streaming platforms such as Apache Kafka can be processed and analyzed in real time with Flink. For this purpose, Flink provides a wide range of interfaces and libraries for different use cases, including SQL, Python and Java/Scala. Apache Flink runs as a cluster, making it highly scalable.

Apache Flink offers

  • seamless handling of large amounts of data
  • Near-real-time reactivity to events
  • high availability and scalability
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Apache Flink is an open-source streaming platform that offers a variety of features, including stream and batch data processing, real-time analytics, and machine learning. Here are three defining components of Apache Flink:

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High performance

Apache Flink offers high performance when processing large amounts of data in real time. Flink uses a tidy architecture that allows data to be processed in parallel, resulting in faster processing speed and better scalability.

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Apache Flink provides a wide range of features that allow developers to create streaming and batch applications that can run on multiple platforms. Flink provides APIs in Java, Scala, Python, and SQL.

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Integrating Flink with your existing applications is easy and seamless, as it works with other systems to simplify the integration of your data flow to Flink. Flink provides extensive integration with Apache Kafka products.

As a Confluent partner for Apache Kafka and Flink, we help organizations future-proof their IT infrastructures using powerful and modern technologies.

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IT Consulting

To ensure that the various functions of Apache Flink are optimally deployed and used, we analyze your existing IT infrastructure and find the right solution.

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Fast implementation

Our experienced developers bring great expertise in Apache Kafka and Flink and help you implement your first Flink use cases as well as production grade streaming data pipelines.

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In our workshops on Apache Flink, we demonstrate the benefits and features of the software and teach how to use it safely and efficiently in business operations.

When processing large amounts of data quickly, the right software is needed. As a powerful framework in the Apache environment, Flink has many advantages to offer:

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Stream and Batch Processing

Apache Flink is able to handle continuous as well as static datasets and process them instantly.

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Flexible scalability

Apache Flink can run in large Big Data environments in addition to individual servers and can be scaled to meet requirements.

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Real-time processing

With Apache Flink, data can be processed in real time and at a high speed to make it quickly available for further use.

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Easy integration

The open source software can be combined with many different technologies and seamlessly integrated with Big Data tools such as Apache Kafka.

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Machine Learning

The libraries included in Apache Flink provide machine learning capabilities to develop and train robust ML models in real-time.

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Low latency

Apache Flink uses a pipelined architecture with data streaming and in-memory processing, enabling it to process data in real-time with low latency.

Frequently asked questions

What is Apache Flink?

Apache Flink is a stream processor framework from the Apache Foundation and is used to perform computations and processing on data streams. The open-source engine can run in almost any environment and can be easily adapted and scaled to meet various requirements to do so.

What is Apache Flink used for?

Apache Flink is an open source distributed computing framework that is used in a variety of applications. It is particularly suited for real-time data processing, batch processing, stream analysis, and event-based applications. Apache Flink can integrate with other Big Data technologies such as Apache Hadoop, Apache Kafka and Apache Spark. It also provides extensive integration with various databases, including Apache Cassandra, Apache HBase, Elasticsearch, Amazon S3, MySQL and PostgreSQL, to read and write data. Overall, Apache Flink is a powerful framework for processing Big Data in real-time and batch mode that is used by many companies and organizations around the world.

How does Apache Flink work?

Apache Flink uses pipelined parallelism to process batch data and dataflow processing for real-time streaming. Mini-batches provide low latency. Additional features such as fault tolerance and memory management ensure efficient and reliable data processing.