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Top 23 Workflow engine Open-Source Projects
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luigi
Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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Kedro
Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
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Flowable (V6)
A compact and highly efficient workflow and Business Process Management (BPM) platform for developers, system admins and business users.
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kestra
Infinitely scalable, event-driven, language-agnostic orchestration and scheduling platform to manage millions of workflows declaratively in code.
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awesome-argo
A curated list of awesome projects and resources related to Argo (a CNCF graduated project)
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uTask
µTask is an automation engine that models and executes business processes declared in yaml. ✏️📋
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titanoboa
Titanoboa makes complex workflows easy. It is a low-code workflow orchestration platform for JVM - distributed, highly scalable and fault tolerant.
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couler
Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
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Project mention: Building in Public: Leveraging Tublian's AI Copilot for My Open Source Contributions | dev.to | 2024-02-12Contributing to Apache Airflow's open-source project immersed me in collaborative coding. Experienced maintainers rigorously reviewed my contributions, providing constructive feedback. This ongoing dialogue refined the codebase and honed my understanding of best practices.
Project mention: Ask HN: What is the correct way to deal with pipelines? | news.ycombinator.com | 2023-09-21I agree there are many options in this space. Two others to consider:
- https://airflow.apache.org/
- https://github.com/spotify/luigi
There are also many Kubernetes based options out there. For the specific use case you specified, you might even consider a plain old Makefile and incrond if you expect these all to run on a single host and be triggered by a new file showing up in a directory…
Project mention: Prefect: A workflow orchestration tool for data pipelines | news.ycombinator.com | 2024-03-13
Like Argo Workflows?
https://github.com/argoproj/argo-workflows
Project mention: Show HN: Hatchet – Open-source distributed task queue | news.ycombinator.com | 2024-03-08
I don't know if I agree with the argument regarding durability vs elastic execution. If I can get both (with a nice API/DX) via something like Temporal (https://github.com/temporalio/temporal), what's the drawback here?
Interesting, thanks for sharing. I'll definitely take a look, although at this point I am so comfortable with Snakemake, it is a bit hard to imagine what would convince me to move to another tool. But I like the idea of composable pipelines: I am building a tool (too early to share) that would allow to lay Snakemake pipelines on top of each other using semi-automatic data annotations similar to how it is done in kedro (https://github.com/kedro-org/kedro).
Kestra's communication is asynchronous and based on a queuing mechanism. It leverages the Micronaut framework and offers two runners: one that uses a database (JDBC) for both the message queue and resource storage, and another that uses Kafka as the message queue and Elasticsearch as the resource storage. The platform is fully extensible and plugin-based, providing a rich set of plugins for various workflow tasks, triggers, and data storage options. For those interested, the GitHub repository is available here: https://github.com/kestra-io/kestra
Project mention: Devtron - End-to-End Software Delivery for Kubernetes Applications | /r/kubernetes | 2023-10-05
Hatchet (https://hatchet.run) | New York City | Full-time
We're hiring a founding engineer to help us with development on our open-source, distributed task queue: https://github.com/hatchet-dev/hatchet.
We recently launched on HN, you can check out our launch here: https://news.ycombinator.com/item?id=39643136. We're two second-time YC founders in this for the long haul and we are just wrapping up the YC W24 batch.
As a founding engineer, you'll be responsible for contributing across the entire codebase. We'll compensate accordingly and with high equity. It's currently just the two founders + a part-time contractor. We're all technical and contribute code.
Stack: Typescript/React, Go and PostgreSQL.
To apply, email alexander [at] hatchet [dot] run, and include the following:
1. Tell us about something impressive you've built.
2. Ask a question or write a comment about the state of the project. For example: a file that stood out to you in the codebase, a Github issue or discussion that piqued your interest, a general comment on distributed systems/task queues, or why our code is bad and how you could improve it.
Project mention: Ask HN: Anyone use a code to mindmap/flowchart tool? | news.ycombinator.com | 2024-02-24https://github.com/django-extensions/django-extensions/blob/...
viewflow supports BPMN: https://github.com/viewflow/viewflow
> It's been a while since you can rerun/resume Nextflow pipelines
Yes, you can resume, but you need your whole upstream DAG to be present. Snakemake can rerun a job when only the dependencies of that job are present, which allows to neatly manage the disk usage, or archive an intermediate state of a project and rerun things from there.
> and yes, you can have dry runs in Nextflow
You have stubs, which really isn't the same thing.
> I have no idea what you're referring to with the 'arbitrary limit of 1000 parallel jobs' though
I was referring to this issue: https://github.com/nextflow-io/nextflow/issues/1871. Except, the discussion doesn't give the issue a full justice. Nextflow spans each job in a separate thread, and when it tries to span 1000+ condor jobs it die with a cryptic error message. The option of -Dnxf.pool.type=sync and -Dnxf.pool.maxThreads=N prevents the ability to resume and attempts to rerun the pipeline.
> As for deleting temporary files, there are features that allow you to do a few things related to that, and other features being implemented.
There are some hacks for this - but nothing I would feel safe to integrate into a production tool. They are implementing something - you're right - and it's been the case for several years now, so we'll see.
Snakemake has all that out of the box.
Maybe it would help you to look at the galaxy project: GitHub main site
author seems to be describing the kind of patterns you might make with https://argoproj.github.io/argo-workflows/ . or see for example https://github.com/couler-proj/couler , which is an sdk for describing tasks that may be submitted to different workflow engines on the backend.
it's a little confusing to me that the author seems to object to "pipelines" and then equate them with messaging-queues. for me at least, "pipeline" vs "workflow-engine" vs "scheduler" are all basically synonyms in this context. those things may or may not be implemented with a message-queue for persistence, but the persistence layer itself is usually below the level of abstraction that $current_problem is really concerned with. like the author says, eventually you have to track state/timestamps/logs, but you get that from the beginning if you start with a workflow engine.
i agree with author that message-queues should not be a knee-jerk response to most problems because the LoE for edge-cases/observability/monitoring is huge. (maybe reach for a queue only if you may actually overwhelm whatever the "scheduler" can handle.) but don't build the scheduler from scratch either.. use argowf, kubeflow, or a more opinionated framework like airflow, mlflow, databricks, aws lamda or step-functions. all/any of these should have config or api that's robust enough to express rate-limit/retry stuff. almost any of these choices has better observability out-of-the-box than you can easily get from a queue. but most importantly.. they provide idioms for handling failure that data-science folks and junior devs can work with. the right way to structure code is just much more clear and things like structuring messages/events, subclassing workers, repeating/retrying tasks, is just harder to mess up.
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Workflow engine related posts
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Show HN: Workflow Orchestrator in Golang
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Building in Public: Leveraging Tublian's AI Copilot for My Open Source Contributions
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When "letting it crash" is not enough
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How To Collect Temporal.io Logs Using Axiom And Pino
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Ask HN: How have you implemented human-in-the-loop workflows?
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Navigating Week Two: Insights and Experiences from My Tublian Internship Journey
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Which queue System you prefer for ecommerce and PS
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A note from our sponsor - SaaSHub
www.saashub.com | 10 May 2024
Index
What are some of the best open-source Workflow engine projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | Airflow | 34,627 |
| 2 | luigi | 17,356 |
| 3 | Prefect | 14,724 |
| 4 | argo | 14,342 |
| 5 | conductor | 10,688 |
| 6 | temporal | 9,940 |
| 7 | Kedro | 9,374 |
| 8 | Flowable (V6) | 7,422 |
| 9 | kestra | 6,528 |
| 10 | Workflow Core | 5,084 |
| 11 | devtron | 3,871 |
| 12 | hatchet | 3,228 |
| 13 | zeebe | 3,038 |
| 14 | viewflow | 2,562 |
| 15 | nextflow | 2,551 |
| 16 | awesome-argo | 1,798 |
| 17 | galaxy | 1,315 |
| 18 | uTask | 1,107 |
| 19 | scipipe | 1,053 |
| 20 | goflow | 1,035 |
| 21 | Gush | 1,024 |
| 22 | titanoboa | 905 |
| 23 | couler | 890 |
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