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Alternatives to Windmill

We are aware other frameworks exist out there. Some of them might suit your specific needs. We believe Windmill is the only solution to provide this comprehensive set of features while being fully open-source.

Out of transparency, here is our subjective impression on other players you might come across.

No-code solutions​

These names are well-known to the general public and have contributed to growing awareness in the workflow building space. They are made for operational teams, have polished UIs but are limited in terms of use cases, power & flexibility. We do not compare ourselves to them.

examples: Zapier or Make

Code-based workflow engines​

On the opposite side, you could go with a solely code-based solution. They give a solid foundation for building workflows, and the workflow lives in version control alongside the rest of your code. What they do not give you is anything above the workflow itself: none of them ships a UI builder, so internal tooling stays a separate problem solved by a separate tool.

On execution overhead we publish benchmarks against Airflow, Prefect, Temporal, Kestra and Hatchet, with the setup and the code used for each engine, rather than assert a number here.

examples: Temporal, Airflow, Prefect, Dagster, Hatchet

More details

Airflow and Temporal are the golden standards. They are very good, battle-tested and scale well. They brought all the good abstractions for workflows and from a bird's eye perspective, we are all running DAGs of tasks, sorted in topological order, parallelized where possible and run by a fleet of workers.


Those frameworks are a great source of inspiration for us but we bring a more principled and more opinionated approach so that one can focus on writing scripts rather than becoming a workflow engine expert. The goal of Windmill is to bring the benefits of those workflow engines in a more accessible package that is fit not just for data engineers but for hybrid teams made of data scientists, ops, and software engineers with standard scripts in Python/TypeScript/Go/PHP/Bash/Rust/C# and low-code builder for the graph itself the common denominator, without any sacrifice on performance (we publish benchmarks against those frameworks, more on the runtime in [1]), features, scalability/reliability and by improving the debuggability and developer experience of those. It is also possible to define workflows-as-code, in the same way as Prefect or Airflow (writing a program that defines the jobs and their dependencies, and then execute that program).


From a tech stack perspective, we rely on the ACID properties of PostgreSQL to achieve persistence and transactionality of the workflow's state. We made the simplifying assumption to be an at-least-once workflow engine, where in the exceptionally rare events of an infrastructure crash (machine shutdown, network split, etc), we will recover automatically but it is up to the application developer to implement idempotency in parts where it is critical for everything else, we support the same feature set (retries, error handler, suspend/sleep, approval steps, cancellation, inner workflows).


To do a fair comparison, looking at the quickstart is a great way to see the different orientation of the product. The Airflow quickstart is a great starting point. One has to learn what is an Airflow pipeline before being able to create or edit them. They also do not provide a great way to debug locally and iterate on those pipelines. You have to write them, deploy them, and then test them. By comparison, in Windmill you can write scripts locally, or test them either step by step or the full flow in the web UI.


Temporal is an SDK for workflows, meaning you have to code around their SDK and learn their abstractions. It is made for teams of software engineers that want to control very finely the execution of the workflow. Their documentation has good examples of that. Temporal is top notch, but it is complex and their primary language support is Go.


By comparison, in Windmill one would just write the canonical python or typescript scripts, exposing just a main function and build a dag in the low-code builder.


[1]: Windmill is not just a workflow engine, it is also a function as a service (FaaS) infrastructure where it can run arbitrary scripts in TypeScript/Python/Bash/Go/PHP/Rust/C#. Contrary to Lambda or GCP cloud functions, we do not need the functions to be pre-packaged and deployed in advance AOT. For TypeScript, we rely on the Bun runtime (Deno is also supported), whose fast startup and aggressive dependency caching keep cold starts minimal. For Python, we have implemented our own dependency resolver that will override the Python virtual path and create a unique virtual environment for that specific script that will respect the lockfile generated at time of saving the script/flow for reproducibility. Given that those are interpreted languages, we pay no performance penalty to interpret that code on demand. So the only limiting factor for task execution is that in the events that dependencies are not cached by the worker, they need to be installed at time of execution. With a limited number of workers, the likelihood of a cache miss is low as soon as one script/workflow is executed more than once. With a large fleet of workers, cache miss increase and hence we have implemented a global caching mechanism that relies on syncing the cache through S3. It is only available in our Enterprise Edition. With it in place, we run tasks and workflows with 0 overhead versus running the same scripts on bare-metal. You can even leverage hardware acceleration without any additional configuration.

Windmill compared to Prefect
Windmill gives more control than Prefect for building & monitoring flows from a single platform.
Windmill compared to Kestra
Windmill provides a natural developer experience.

Prefect and Dagster​

Prefect acquired Dagster Labs in July 2026, and the combined company operates under the Prefect name from August 2026. Both products continue: Dagster keeps its name, its open-source project stays under its existing license and is still being developed, and Dagster+ deployments, contracts, pricing and support are unchanged.

For anyone choosing today that is one fewer independent vendor, not one fewer product. The two authoring models are still different, Prefect wrapping Python functions as flows and tasks and Dagster describing a graph of assets, so we keep a comparison for each: Windmill vs Prefect and Windmill vs Dagster.

Transformation layer​

dbt is not an orchestrator. It compiles a set of SQL models into a DAG and runs them against your warehouse; something else still has to schedule that run, react to it and put the rest of the pipeline around it. That is where it overlaps with everything above.

Windmill runs dbt rather than replacing it. A dbt project is a script language of its own: the project is unmodified, it runs on your own workers, and its models land on the same asset graph as the Python and DuckDB scripts around them. So the comparison is not really with dbt Core, it is with dbt Cloud and with orchestrating dbt from Airflow.

examples: dbt

Admin panels builders​

Getting closer to Windmill. Those players have a blend on admin panels. Therefore they are strong on UIs and low-code features. They allow you to use code in the process. However we believe they lack flexibility for building complex workflows.

Those are great tools and since they focus solely on the UI builder part, they have made it a great and mature product. On the other hand, Windmill UI builder integrates well with the workflow and script execution engine.

If you were to choose Windmill for the workflow engine, we hope to convince you that it might be worth the switch later for the UI builder part given our high level of integrations between those layers and us having caught up with them on the UI builder part.

examples: Retool and its open source alternatives Tooljet, Appsmith & Openblocks

Windmill compared to Retool
Windmill provides a more versatile and powerful framework than Retool.

Workflow builders​

n8n​

n8n is source-available but not open-source: it ships under the Sustainable Use License, which limits use to your own internal business purposes or to non-commercial and personal use. It has no app builder, and it is not centered on organizing your scripts but on assembling workflows out of pre-made integrations to external services, with code inlined in Code nodes.

Its Code node runs JavaScript on Node.js and, since native Python landed on task runners, Python. Dependencies are not per-node in either language: npm modules have to be enabled instance-wide on a self-hosted n8n, Python packages have to be present in the n8nio/runners image and explicitly allowlisted, and on n8n Cloud neither can be imported at all.

For a detailed side-by-side, see the Windmill vs n8n comparison.

Pipedream​

Pipedream has no app builder, it is centered on integrations to external services, and it is hosted only: there is no self-hosted deployment of the platform. Its component registry is public, but under the Pipedream Source Available License rather than an open-source one, since the license excludes "any commercial use of the software". Code steps run Node.js, Python, Go and Bash.

Workday signed a definitive agreement to acquire Pipedream in November 2025.

Hatchet​

Hatchet is a newer entrant, launched in 2024. It is a Postgres-backed task queue and workflow engine, with SDKs for Python, TypeScript, Go and Ruby. In our benchmarks it performed well on long-running tasks, with high execution ratios and low overhead, and struggled in multi-worker lightweight scenarios, with high wait and idle times despite perfect task distribution.

The difference with Windmill is scope more than speed. Hatchet is the engine that your own worker programs register against; Windmill also owns the editor, the auto-generated UIs, the app builder and 20+ script languages.

Kestra​

Kestra offers a declarative YAML syntax and event-driven orchestration, with a focus on data pipelines. In our benchmarks it sat in the mid-tier: decent on long-running tasks, slower orchestration on short task loads, more predictable than Airflow or Prefect but less optimized than Temporal, Hatchet or Windmill.

Its plugin ecosystem and its backfills are the strong points. What it does not cover is the internal tooling around the pipelines, which is where Windmill combines workflows, apps and scripts on one platform.

For a detailed side-by-side, see the Windmill vs Kestra comparison.

Interactive side-by-side comparisons​

Windmill vs Airflow
Compare authoring, scheduling, and execution between Windmill and Airflow.
Windmill vs Temporal
Compare workflow SDK ergonomics, durability, and observability.
Windmill vs Prefect
Compare flow authoring, deployment, and runtime between Windmill and Prefect.
Windmill vs Kestra
Compare YAML-first orchestration with Windmill's script-first model.
Windmill vs n8n
Compare node-based automation with Windmill's code-first workflow engine.
Windmill vs Retool
Compare internal-tool builders and how each handles backend logic.
Windmill vs Dagster
Compare data orchestration and asset-based pipelines with Windmill's approach.
Windmill vs dbt
Compare SQL transformation workflows and how Windmill runs dbt-style pipelines.

What makes Windmill different today​

We are working to build a solution with a clear approach (targeting developers who do not want to compromise on flexibility) and the aim to solve main issues (scalability, technicity for advanced use cases, open-source).

We believe Windmill is different because:

Windmill keeps evolving quickly: AI Flow Chat for natural language workflow creation, data pipelines with DuckLake and DuckDB support, client SDKs in TypeScript, Python and Rust, and enterprise capabilities like the customer portal and autoscaling.

Have a look at our core concepts and changelog to see what makes us different.

We ourselves have our own limitations. We believe we can do better in terms of product education and having a prettier UI. All the rest is ready for scale.

Please note that this comparison is made with at least two biases: 1. we want to convince you of the power of our product and 2. we are never safe from hiding things from ourselves about the strengths of competitors.

Anyway, we are committed to the culture of transparency and of confronting the facts, so if you have any objections or suggestions, please contact us at contact@windmill.dev.