Build data pipelines, the easy way 🛠️ (by orchest)

Orchest Alternatives

Similar projects and alternatives to orchest

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better orchest alternative or higher similarity.

orchest reviews and mentions

Posts with mentions or reviews of orchest. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-12-06.
  • Building container images in Kubernetes, how would you approach it?
    2 projects | /r/kubernetes | 6 Dec 2022
    The code example is part of our ELT/data pipeline tool called Orchest: https://github.com/orchest/orchest/
    2 projects | /r/kubernetes | 6 Dec 2022
  • Launch HN: Patterns (YC S21) – A much faster way to build and deploy data apps
    6 projects | news.ycombinator.com | 30 Nov 2022
    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

  • Argo became a graduated CNCF project
    3 projects | /r/kubernetes | 27 Nov 2022
    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).
  • How do you deal with parallelising parts of an ML pipeline especially on Python?
    5 projects | /r/mlops | 12 Aug 2022
    We automatically provide container level parallelism in Orchest: https://github.com/orchest/orchest
  • Prefect vs other things question
    2 projects | /r/mlops | 3 Aug 2022
    If you’re looking for something with a great UI experience you can check out our open source project called Orchest. It might be what you seek from a simplicity perspective. https://github.com/orchest/orchest
  • Airflow's Problem
    6 projects | news.ycombinator.com | 2 Aug 2022
    Argo is pretty amazing if you want to take advantage of the work Kubernetes has done to scale resource efficiently across a cluster of compute nodes.

    If you’re looking for something that’s a bit more high level and friendly to expose directly to your data team (data scientists/data engineers/data analysts) you can check out https://github.com/orchest/orchest

    You can think of it as a browser UI/workbench for Argo scheduled pipelines. Disclaimer: author of the project

  • How are you guys validating your data?
    2 projects | /r/dataengineering | 9 Jun 2022
    +1 on a lightweight version of GE to more easily make part of an existing pipeline. Would like it for internal use (our data pipelines), but also for our open source users (https://github.com/orchest/orchest).
  • Apache Hop 2.0
    4 projects | news.ycombinator.com | 8 Jun 2022
  • I reviewed 50+ open-source MLOps tools. Here’s the result
    3 projects | /r/mlops | 28 May 2022
    You might want to add https://github.com/orchest/orchest/ to the Pipeline orchestration category (disclaimer: I work at the company making it)
  • A note from our sponsor - InfluxDB
    www.influxdata.com | 22 Feb 2024
    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. Learn more →


Basic orchest repo stats
9 months ago

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.

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