Among the provided options, Cloud Composer stands out as the most appropriate cloud-native service for orchestrating the entire pipeline. It is a fully managed workflow orchestration service that enables the creation, scheduling, and monitoring of workflows across diverse cloud services and on-premises resources. With its extensive array of pre-built connectors to various cloud providers such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure, Cloud Composer is perfectly suited for businesses with a hybrid cloud approach. Additionally, it offers an intuitive interface for workflow construction and monitoring, supporting both Apache Airflow and Kubernetes for workflow management flexibility. Conversely, Cloud Dataflow specializes in executing batch and streaming data processing pipelines, Cloud Dataproc is tailored for running Apache Hadoop and Apache Spark jobs on clusters, and Cloud Dataprep focuses on data preparation tasks like exploring, cleaning, and transforming data. While these services excel in their respective areas, they lack the comprehensive orchestration capabilities required for managing a data pipeline that spans multiple cloud services and on-premises resources.