Apache Beam and Apache Flink are both distributed computing frameworks for processing large amounts of data in parallel, but they have some fundamental differences in their design and functionality.
Apache Beam is a unified programming model for batch and streaming data processing, which provides a high-level API that allows developers to write data processing pipelines that can run on various execution engines, including Apache Flink, Apache Spark, and Google Cloud Dataflow. Beam provides a set of primitives for building data processing pipelines, including data sources, transformations, and sinks, and it supports multiple data formats and languages.
On the other hand, Apache Flink is a distributed data processing framework that provides low-latency and high-throughput processing of streaming and batch data. Flink supports various data sources, including file systems, messaging systems, and databases, and it provides a set of operators for data transformations, such as filtering, mapping, and aggregating. Flink also provides features for managing state, handling failures, and optimizing performance.
One of the main differences between Apache Beam and Apache Flink is their execution model. Beam provides a portable execution model that allows pipelines to be run on different execution engines, while Flink provides its own execution engine optimized for low-latency processing of streaming data. Another difference is their level of abstraction. Beam provides a high-level API that abstracts away the details of the underlying execution engine, while Flink provides a low-level API that gives developers more control over the execution details.
Overall, Apache Beam is a more flexible and portable framework for building data processing pipelines that can be run on different execution engines, while Apache Flink is a more specialized framework for low-latency and high-throughput processing of streaming data with a more granular level of control.