How Google Cloud Workflows Compares to Other Cloud Workflow Services

What Google Cloud Workflows is

According to Google's documentation, Workflows combines services such as custom services on Cloud Run or Cloud Run functions, Google Cloud services like BigQuery, and any HTTP-based API into one defined sequence. A workflow is a series of steps written in YAML or JSON. It is serverless, scales as needed and charges nothing while idle, and Google's product page describes pricing as paying only when workflows take steps.

You can run a workflow from the Google Cloud console, the command line, client libraries, or by sending an HTTP POST request to its invocation URL. The console also offers visualization while you edit. Connectors make it simpler to call other Google Cloud APIs, handling details like request formatting, retries and waiting for long-running operations.

One point worth knowing before you compare anything: Google lists business processes among the use cases, "including conditions, actions, and human-in-the-loop events", and describes HTTP callbacks as useful for waiting on external systems and for human-in-the-loop processes. So Workflows can model a process with a person in it. What that takes in practice is covered in the section on people in the process.

How it compares at a glance

The table lists what each service says it is, how you build with it, and what to keep in mind. It is drawn from each vendor's own documentation, so the descriptions are theirs, and it does not rank the services, because they are built for different jobs.

Workflows vs AWS Step Functions

These two are the closest pair, and Google says so itself. In its guide for people migrating from Step Functions, Google describes both as fully managed, state-based orchestration platforms that run services in the order you define, and notes that both model a workflow as a series of tasks: steps in Workflows and states in Step Functions.

The differences are mostly in how you author and where you live. Step Functions primarily uses JSON and does not support YAML directly, although YAML is possible through the AWS Toolkit for Visual Studio Code and AWS CloudFormation. Step Functions offers a visual Workflow Studio, while Workflows is edited in the Google Cloud console or from the command line. Step Functions also has two workflow types, Standard and Express, and Google's guide sets Express aside because of its limited duration and lack of exactly-once execution.

The practical decision is usually not a feature comparison. It is which cloud your services already run on, because each service is designed to orchestrate its own cloud's services first.

Workflows vs Cloud Composer

Google publishes a page specifically on choosing between these two, and its core point is that they support different architectures. Workflows orchestrates HTTP-based services into a durable, stateful workflow. Cloud Composer is designed to orchestrate data-driven workflows, particularly ETL and ELT, and is a fully managed version of Apache Airflow where all logic is written in Python as DAG definition files.

Composer also has a large operator library, with more than 150 operators for Google Cloud alone. If your workflow is a data pipeline, that points to Composer. If it is a sequence of service calls, it points to Workflows.

Workflows vs Azure Logic Apps

This pair differs most in who is expected to build. Microsoft describes Logic Apps as low-code and no-code tooling, where you usually don't write code, though you can run your own when you need to. It comes in two resource types: a Consumption logic app, which supports a single workflow in multitenant Azure, and a Standard logic app, which supports multiple workflows in single-tenant Azure.

Workflows, by contrast, is defined as text in YAML or JSON, which suits developers and platform teams. If the people who will maintain the workflow are not developers, that difference matters more than any feature in the table.

Where Temporal fits

Temporal is a different kind of tool, and it is worth naming because it appears in many comparisons. Its documentation describes a platform that guarantees the durable execution of your application code, meaning a workflow keeps its state and progress through failures and outages. You write the workflow in a general-purpose language through an SDK, and you can self-host the service or use Temporal Cloud.

That makes it a fit for long-running application logic written by developers, rather than a managed way to chain service calls or to build a business process without code.

When the process has people in it

Everything above assumes the workflow is a technical one: services calling services. A lot of real workflows are not. They are approvals, reviews and requests, where a person has to say yes before the next step. This is where the choice changes.

It is also where a common mix-up happens. Someone without a technical background can find "Google Cloud Workflows", see the word workflows, and assume it is a tool for automating a business process. It isn't really that: it is infrastructure-level orchestration, closer to code and primitives than to an automation platform with forms and approvals. Teams that automate business processes rarely pick it for that job at all. So if what you have is a request that needs a person's sign-off, the comparison that matters is not Workflows against Step Functions, it is a service like these against a no-code automation platform.

Google Cloud Workflows can pause and wait for an HTTP callback, and Google describes that as the way to implement human-in-the-loop steps. Our reading is that a callback gives you the pause and the resume point. The request that tells someone there is something to approve, the screen where they click, the reminder when they don't, the escalation when they are away and the record of who decided are things you build or bring from another tool. For a team of developers that is reasonable. For an IT or operations team that wants to change an approval rule without a deployment, it is a lot to own.

That is the case for a no-code workflow tool built around Google Workspace, and Zenphi is one. It routes approvals sequentially, in parallel or by condition, lets people decide in Gmail or Google Chat, calls Google Workspace administration actions, and keeps an audit record, without writing code. One team at Google, the Google Cloud Space in Munich, uses it to automate Workspace administration, according to our case study.

The honest framing is that these are tools for different tasks, not competitors. Google Cloud Workflows orchestrates services; a no-code workflow tool runs the business process with the people in it. In practice they rarely even meet, because teams that reach for Cloud Workflows are usually making API calls inside Google Cloud, not automating an approval. If you do need the two to talk, Zenphi can send and receive HTTP requests, including an HTTP trigger that starts a workflow when a request comes in, so one side can call the other. But most of the time the real question is simply which of the two your task is, not how to join them.

Which kind of workflow do you have?

Pick what you want to orchestrate. The tool shows which kind of service fits each one, following the comparisons above. You may need more than one, and it is a starting point rather than a verdict.

FAQ

Sources

• Google Cloud — Workflows overview
• Google Cloud — Workflows product page
• Google Cloud — Choose Workflows or Cloud Composer for service orchestration
• Google Cloud — Migrate from AWS Step Functions to Workflows
• Google Cloud — Cloud Composer FAQ
• AWS — Step Functions Developer Guide
• Microsoft Learn — Azure Logic Apps overview
• Temporal — Durable execution
• Google for Developers — Directory API (Admin SDK)
• Zenphi — Approval workflow software for Google Workspace
• Zenphi — Google Cloud Space case study

Pages were checked on October 15, 2026 and can change. We did not test these services, so their descriptions follow each vendor's own documentation. Where we offer our own reading, we say so. The Zenphi pages and case study are our own, so read their claims with that in mind.