Apache Beam provides a framework for running batch and streaming data processing jobs that run on a variety of execution engines. Several of the TFX libraries use Beam for running tasks, which enables a high degree of scalability across compute clusters. Beam includes support for a variety of execution engines or "runners", including a direct runner which runs on a single compute node and is very useful for development, testing, or small deployments. Beam provides an abstraction layer which enables TFX to run on any supported runner without code modifications. TFX uses the Beam Python API, so it is limited to the runners that are supported by the Python API.
Deployment and Scalability
As workload requirements increase Beam can scale to very large deployments across large compute clusters. This is limited only by the scalability of the underlying runner. Runners in large deployments will typically be deployed to a container orchestration system such as Kubernetes or Apache Mesos for automating application deployment, scaling, and management.
See the Apache Beam documentation for more information on Apache Beam.