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Orchest Alternatives
Similar projects and alternatives to orchest
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CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
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n8n
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
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cli
Official Command Line Interface for the IPinfo API (IP geolocation and other types of IP data) (by ipinfo)
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QEMU
Official QEMU mirror. Please see https://www.qemu.org/contribute/ for how to submit changes to QEMU. Pull Requests are ignored. Please only use release tarballs from the QEMU website.
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SaaSHub
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PostHog
🦔 PostHog provides open-source web & product analytics, session recording, feature flagging and A/B testing that you can self-host. Get started - free.
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windmill
Open-source developer platform to power your entire infra and turn scripts into webhooks, workflows and UIs. Fastest workflow engine (13x vs Airflow). Open-source alternative to Retool and Temporal.
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dbt-core
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
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Gravitational Teleport
The easiest, and most secure way to access and protect all of your infrastructure.
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Baserow
Open source no-code database and Airtable alternative. Create your own online database without technical experience. Performant with high volumes of data, can be self hosted and supports plugins (by bramw)
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Lean and Mean Docker containers
Slim(toolkit): Don't change anything in your container image and minify it by up to 30x (and for compiled languages even more) making it secure too! (free and open source)
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toc
⚖️ The CNCF Technical Oversight Committee (TOC) is the technical governing body of the CNCF Foundation.
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hookdeck-cli
Alternative to ngrok for localhost asynchronous web development (e.g. webhooks). No account required.
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SaaSHub
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orchest discussion
orchest reviews and mentions
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Decent low code options for orchestration and building data flows?
You can check out our OSS https://github.com/orchest/orchest
- Build ML workflows with Jupyter notebooks
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Building container images in Kubernetes, how would you approach it?
The code example is part of our ELT/data pipeline tool called Orchest: https://github.com/orchest/orchest/
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Launch HN: Patterns (YC S21) – A much faster way to build and deploy data apps
First want to say congrats to the Patterns team for creating a gorgeous looking tool. Very minimal and approachable. Massive kudos!
Disclaimer: we're building something very similar and I'm curious about a couple of things.
One of the questions our users have asked us often is how to minimize the dependence on "product specific" components/nodes/steps. For example, if you write CI for GitHub Actions you may use a bunch of GitHub Action references.
Looking at the `graph.yml` in some of the examples you shared you use a similar approach (e.g. patterns/openai-completion@v4). That means that whenever you depend on such components your automation/data pipeline becomes more tied to the specific tool (GitHub Actions/Patterns), effectively locking in users.
How are you helping users feel comfortable with that problem (I don't want to invest in something that's not portable)? It's something we've struggled with ourselves as we're expanding the "out of the box" capabilities you get.
Furthermore, would have loved to see this as an open source project. But I guess the second best thing to open source is some open source contributions and `dcp` and `common-model` look quite interesting!
For those who are curious, I'm one of the authors of https://github.com/orchest/orchest
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Argo became a graduated CNCF project
Haven't tried it. In its favor, Argo is vendor neutral and is really easy to set up in a local k8s environment like docker for desktop or minikube. If you already use k8s for configuration, service discovery, secret management, etc, it's dead simple to set up and use (avoiding configuration having to learn a whole new workflow configuration language in addition to k8s). The big downside is that it doesn't have a visual DAG editor (although that might be a positive for engineers having to fix workflows written by non-programmers), but the relatively bare-metal nature of Argo means that it's fairly easy to use it as an underlying engine for a more opinionated or lower-code framework (orchest is a notable one out now).
- Ideas for infrastructure and tooling to use for frequent model retraining?
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Looking for a mentor in MLOps. I am a lead developer.
If you’d like to try something for you data workflows that’s vendor agnostic (k8s based) and open source you can check out our project: https://github.com/orchest/orchest
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Is there a good way to trigger data pipelines by event instead of cron?
You can find it here: https://github.com/orchest/orchest Convenience install script: https://github.com/orchest/orchest#installation
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How do you deal with parallelising parts of an ML pipeline especially on Python?
We automatically provide container level parallelism in Orchest: https://github.com/orchest/orchest
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Launch HN: Sematic (YC S22) – Open-source framework to build ML pipelines faster
For people in this thread interested in what this tool is an alternative to: Airflow, Luigi, Kubeflow, Kedro, Flyte, Metaflow, Sagemaker Pipelines, GCP Vertex Workbench, Azure Data Factory, Azure ML, Dagster, DVC, ClearML, Prefect, Pachyderm, and Orchest.
Disclaimer: author of Orchest https://github.com/orchest/orchest
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A note from our sponsor - SaaSHub
www.saashub.com | 7 Feb 2025
Stats
orchest/orchest is an open source project licensed under Apache License 2.0 which is an OSI approved license.
The primary programming language of orchest is TypeScript.