[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-09-03。"],[],[],null,["# Choose Workflows or Cloud Composer for service orchestration\n\nBoth [Workflows](/workflows/docs/overview) and\n[Cloud Composer](/composer/docs/concepts/overview) can be used for service\norchestration to combine services to implement application functionality or\nperform data processing. Although they are conceptually similar, each is\ndesigned for a different set of use cases. This page helps you choose the right\nproduct for your use case.\n\nKey differences\n---------------\n\nThe core difference between Workflows and Cloud Composer\nis what type of architecture each product is designed to support.\n\n**Workflows** orchestrates multiple HTTP-based services into a\ndurable and stateful workflow. It has low latency and can handle a high number\nof executions. It's also completely serverless.\n\nWorkflows is great for chaining microservices together,\nautomating infrastructure tasks like starting or stopping a VM, and integrating\nwith external systems. Workflows connectors also support simple\nsequences of operations in Google Cloud services such as Cloud Storage\nand BigQuery.\n\n**Cloud Composer** is designed to orchestrate data driven workflows\n(particularly ETL/ELT). It's built on the Apache Airflow project, but\nCloud Composer is fully managed. Cloud Composer supports your\npipelines wherever they are, including on-premises or across multiple cloud\nplatforms. All logic in Cloud Composer, including tasks and scheduling,\nis expressed in Python as Directed Acyclic Graph (DAG) definition files.\n\nCloud Composer is best for batch workloads that can handle a few\nseconds of latency between task executions. You can use Cloud Composer\nto orchestrate services in your data pipelines, such as triggering a job in\nBigQuery or starting a Dataflow pipeline. You can use\npre-existing operators to communicate with various services, and there are over\n150 operators for Google Cloud alone.\n\nDetailed feature comparison\n---------------------------\n\n*** ** * ** ***\n\n1. [Source code for airflow.models.xcom](https://airflow.apache.org/docs/apache-airflow/stable/_modules/airflow/models/xcom.html).\n *Apache Airflow documentation* . August 2, 2021. [↩](#fnref1)"]]
