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Alternatives

Products that do what I built a backend so simple that it fits in a YAML file does

  1. 1LB
  2. 2IB
  3. 3EA

    eno [1] - A modern plaintext language w/ libraries [2] for JavaScript, Python, Ruby & soon more! We migrated a big relational research database to a file-based solution - requirements were: - Super fast and easy editability for users - Highest performance for parsing/validating >10K documents on every user change. Our trials with YAML/TOML showed us that we wanted something both faster [3][4] and easier [4], something tailored for file-based content management ... and after months of research & development it's now publicly available (under MIT license) for everyone! Last but…

    2018

  4. 4IB
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  6. 6CY
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  10. 10IS

    Everything that would be here is in the README. I hope this gets big, it has tons of potential.

    2013 · github.com

  11. 11IM
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  13. 13IM

    2022 · getquickbase.com

  14. 14BL

    Hello everyone! I am Jan, CTO and one of the creators of Pathway, the real-time data processing framework. I’m excited to share Pathway’s ready-to-use AI Pipelines, configurable with just YAML! These frameworks offer out-of-the-box solutions for AI search, RAG, and more—optimized for real-time indexing and in-memory processing. What makes it simple? YAML templates! The pipeline templates are fully customizable using YAMLs to fit your needs, from changing the data sources to the choice of the LLM model, all without touching Pathway’s Python code. Thanks to the Pathway data processing engine,…

    2024 · pathway.com

  15. 15IM
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  19. 19YY

    2017 · github.com

  20. 20MF

    2012 · docs.dokeeno.com

  21. 21HA

    Demo starts at 50m into the video. This was a bit terrifying to record because 2am the previous night everything was totally broken after a major refactor (so that we could add external LLM support as well as local GPUs). But pressure can be a useful force :-D We start with a stack deployed on my laptop without a GPU, pointing to together.ai so we can run open source LLMs easily without having to have access to a GPU. We show simple inference through the ChatGPT-like web interface (with users, sessions etc) and then simple drag'n'drop RAG. Then we show some helix apps defined as yaml: Marvin…

    2024 · youtube.com

  22. 22YV

    Hi HN, I made a tiny tool called YAML Validator that checks your YAML files with one Docker command — no installs, no setup, no excuses. It does: - Syntax checks - yamllint linting - checkov security scanning - All in one lightweight, zero-config container --------------------------------------------------------- How to use: docker run -v "$(pwd):/data" pooyanazad/yaml-checker Optional alias (for .bashrc / .zshrc): alias ytest='docker run -v "$(pwd):/data" pooyanazad/yaml-checker' Then simply call: ytest sample.yaml YAML powers CI/CD, configs, infra ,and…

    Nov 2025

  23. 23CC

    We're two engineers that got fed up with context switching. Why do we need to do a git push, open a browser tab, wait for some task to actually start, bite nails (or read HackerNews) for 10 minutes or more while dependencies are being installed for the 100th time and finally end up with an invalid YAML error. And for some reason this usually happens in the final stage of the pipeline leading up to the inevitable git commits "Fixed", "Fixed again", "Test", "Really fixed this time". We can do better. We set out to build Zippy. A CI/CD system that works from your terminal. No context…

    Mar 2026 · zippy.sh

  24. 24LA

    You build LLM applications with YAML files, that define an execution graph. Nodes can be either LLM API calls, regular function executions or other graphs themselves. Because you can nest graphs easily, building complex applications is not an issue, but at the same time you don't lose control. The YAML basically states what are the tasks that need to be done and how they connect. Other than that, you only write individual python functions to be called during the execution. No new classes and abstractions to learn.

    2024 · github.com

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