Appwrite is an open source backend server that helps you build native iOS applications much faster with realtime APIs for authentication, databases, files storage, cloud functions and much more! Learn more →
Orchest Alternatives
Similar projects and alternatives to orchest
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ploomber
The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
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Klotho
AWS Cloud-aware infrastructure-from-code toolbox [NEW]. Build cloud backends with Infrastructure-from-Code (IfC), a revolutionary technique for generating and updating cloud infrastructure. Try IfC with AWS and Klotho now (Now open-source)
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n8n
Free and source-available fair-code licensed workflow automation tool. Easily automate tasks across different services.
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label-studio
Label Studio is a multi-type data labeling and annotation tool with standardized output format
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PostHog
🦔 PostHog provides open-source product analytics, session recording, feature flagging and a/b testing that you can self-host.
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Appwrite
Appwrite - The Open Source Firebase alternative introduces iOS support . Appwrite is an open source backend server that helps you build native iOS applications much faster with realtime APIs for authentication, databases, files storage, cloud functions and much more!
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ExpansionCards
Reference designs and documentation to create Expansion Cards for the Framework Laptop
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Gravitational Teleport
The easiest, most secure way to access infrastructure.
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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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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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windmill
Open-source developer platform to turn scripts into workflows and UIs. Open-source alternative to Airplane and Retool.
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InfluxDB
Access the most powerful time series database as a service. Ingest, store, & analyze all types of time series data in a fully-managed, purpose-built database. Keep data forever with low-cost storage and superior data compression.
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.
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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/[email protected]). 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).
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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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Prefect vs other things question
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
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Airflow's Problem
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
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How are you guys validating your data?
+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
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I reviewed 50+ open-source MLOps tools. Here’s the result
You might want to add https://github.com/orchest/orchest/ to the Pipeline orchestration category (disclaimer: I work at the company making it)
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A note from our sponsor - Appwrite
appwrite.io | 9 Jun 2023
Stats
Basic orchest repo stats
44
3,876
9.2
3 days 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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