JOjoloooo·Jul 17, 2025
Would this be something that Activepieces or Kestra could also do?
https://github.com/activepieces/activepieces
https://github.com/kestra-io/kestra
In N8n vs. node-red, which to use for AI workloadskestra-io
kestra
Java2022–2025
kestra-io / kestra
kestra
Orchestrate everything, everywhere. The open-source control plane for workflows across data, infrastructure, business processes and AI agents. Declarative YAML, event-driven, any language, Git-versioned, scalable to millions of executions.
Systems & InfrastructureScience & EngineeringAI & Machine LearningDeveloper ToolsData & DatabasesDevOps & CloudAutomation & Workflows
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30.2KGitHub stars
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Orchestrate everything, everywhere. The open-source control plane for workflows across data, infrastructure, business processes and AI agents. Declarative YAML, event-driven, any language, Git-versioned, scalable to millions of executions.
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| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
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| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 8 | 3 | 5 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2024 | 2024-01-01 00:00:00 UTC | 2025-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2025 | 2025-01-01 00:00:00 UTC | 2026-01-01 00:00:00 UTC | 1 | 0 | 1 |
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https://github.com/kestra-io/kestra
In Kestra is an open-source data orchestration platform for complex workflowsAll the issues described in this post lead me to create Kestra [0] .
Airflow was a true revolution when it was open-source and we need thanks its innovation.
But I totally agree that a large static dag is not appropriate in the actual data world with data mesh and domain responsibility.
[0] https://github.com/kestra-io/kestra
In Airflow's ProblemAsk HN: Open-source with Kafka as dependencies, is this a instant turn off?
We have launched Kestra (https://github.com/kestra-io/kestra), an open source data scheduling and orchestration platform that features high scalability and availability.
To achieve this, we rely on Kafka as our core database.
We have received feedback that Kafka can be difficult to manage and is a no go on the project. The project did not pass the architecture team for this reason.
While you can use Kafka without creating a full cluster (using a single node setup), it seems that Kafka is synonymous with complexity and problems.
We're asking for your thoughts on this. We are thinking of making it easier to onboard the project.
So my question is this:
- Is Kafka really a scary technology, and do you feel like it can be a pain to manage and no go technologies?
- We also depend on ElasticSearch, do you have the same point of view?
- We have
Read the rest
plans to add another option that will replace both dependencies with jdbc (https://github.com/kestra-io/kestra/pull/368), is theses dependencies more comfortable for you?
- If yes, what type of database is required? (mysql, postgres, others)
- We also see that Redis could have all the query interface needed for Kestra, what do you think about this one?
We've done some research and haven't found a cloud database at the moment that could meet all the needs (especially full text search and transaction support), if you have an idea it's welcome.
Thanks for your time, there's a lot of work to build this part, so your feedback is really important to avoid going in the wrong direction.
Damn shame they stepped on the same jinja2-in-yaml landmine as ansible, using "{{" as template markers: https://github.com/kestra-io/kestra/blob/v0.4.2/README.md?pl...
Had they chosen to use "<<" (or "${{" like GHA), it would have removed the need to quote almost every one of those expressions that appear in a yaml scalar context, since "{" is a legal yaml syntax character and thus `alpha: {{ beta }}` is interpreted as '{"alpha":{ ... } }' but with an illegal anonymous inner map
In Open source data orchestration and scheduling platformI don't pitch as more complicated version of Airflow, rather, I think it's more simple than Airflow on the UX side: we use declarative flow with yaml and not python code that can be
I agree with you that Kafka & ElasticSearch can be a pain to scale if you need to have a horizontal and vertical scaling.
On other side, on single machine, it's really has easy to setup. With this, you will have the same scaling than Airflow for exemple since it depend on a non scalable database (mysql or postgres). But the chance you will have with Kestra is that you will be able to scale to multiple node for your backend (as well with kestra that allow scaling all services). When you hit the limit with standard database, you will be stuck.
And yes clearly infinite scale is not a literal statement terms, nothing can scale infinitely but since the architecture
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is really robust (and scalable), the issues will be on other aspects than Kestra (cloud limit, database overload, ...).
A final point and a more important one, the backend are all pluggagle in Kestra since Kestra is really think as module: Look at the directory here : https://github.com/kestra-io/kestra :
- runner-kafka & runner-memory are 2 implementation of Kestra, you can add a new one that will use Redis, Pulsar, ...
- repository-elasticsearch & repository-memory is the same, you can implement another one, I started one implementation for JDBC that I don't have the time to finish for now : https://github.com/kestra-io/kestra/pull/368
The support of windows server seems to be easy I think.
Since it's java behind, most of the api is working on windows.
Just need to create a custom task for windows, added in the backlog : https://github.com/kestra-io/kestra/issues/519
For the desktop app, I don't know, build one with electron can be simple, but a full app is not on the roadmap for now.
What is your usages ?
In Show HN: Kestra - Open-Source Airflow AlternativeShow HN: Kestra - Open-Source Airflow Alternative
Hey HN, I'm really proud to share with you my new open source project: Kestra https://github.com/kestra-io/kestra
I created a few years ago a successful open source AKHQ project: https://github.com/tchiotludo/akhq (renamed from KafkaHQ) which has been adopted by big companies like Best Buy, Pipedrive, BMW, Decathlon and many more. 2300 stars, 120 contributors, 10M docker downloads, much more than I expected.
Now let's talk about Kestra, an infinitely scalable orchestration and scheduling platform for creating, running, scheduling and monitoring millions of complex pipelines.
I started the project 30 months ago and I'm even more proud of this project that required a lot of investment and time to build the future of data pipelines (I hope). The result is now ready to be presented and I hope to get some feedback from you, HN community.
To ha
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ve a fully scalable solution, we choose Kafka as our database (of course, I love Kafka if you didn't know) as well as ElasticSearch, Micronaut, ... and can be deployed on Kubernetes, VM or on premise.
You may think there are many alternatives in this area, but we decided to take a different road by using a descriptive approach (low code) to build your pipelines allowing to edit directly from the web interface and deploy to production with terraform directly. We paid a lot of attention to the scalability and performance part which allows us to have already a big production at a big French retailer: Leroy Merlin
Since Kestra core is plugin based, many are available from the core team, but you can create one easily.
More information:
- on the official website: https://kestra.io/
- on the medium post: https://medium.com/@kestra-io/introducing-kestra-infinitely-...
- check out the project: https://github.com/kestra-io/kestra
Your comments are more than welcome, thank you!
Hi HN,
Im a big fan of Airflow and its advantages on workflow management tools. After many problems of performance on a project I try some new modern platform, prefect dagster. Very good !
And recently I read this medium blog on Kestra a new platform and I decide to try it. It was a good decision because the user experience was cool, easy, efficient and powerful. The engine seems much more advanced to me because the same complex flows are much faster on Kestra than with Prefect.
Take time to interest about and up this project on https://github.com/kestra-io/kestra
In Show HN: Free open-source alternative to Airflow/Prefect/Airbyte/DagsterKestra: Infinitely scalable open source orchestration and scheduling platform
7 points · Open discussion