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Alternatives

Products that do what DataConstruct does

We fake it till you make it

  1. 1DM

    Hello HN, Today we're sharing with you DataConstruct, a tool to help you generate mock data and the code to consume it. Features: - Exporting data to json, yaml, xml - Generating PostgreSQL, MySQL scripts - Code gen for various languages including but not limited to C++, Rust, Typescript, Java, C#, Go, Dart, Swift, Mojo You can try it out at the link below (no signup or credit card needed), the only limit being up to 1000 rows per generation within the playground. https://www.dataconstruct.io/organizations/playground/schema... If there's languages, databases, data…

    2024 · dataconstruct.io

  2. 2
    Struct98

    Your next-generation, all-in-one, NFT launchpad platform

    2022

  3. 3CG
  4. 4
    Structura100

    Visualize and edit JSON like Lego blocks

    Oct 2025

  5. 5

    Turn design into a clean, semantic HTML and CSS code

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  6. 6

    A grid library for instant big data processing

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  7. 7

    The diagramming tool for developers

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  8. 8
    Datalink118

    Populate your design layers with realistic data

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  9. 9FS
  10. 10
    DataMorf135

    Build automated workflows for complex tasks

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  11. 11

    Making the web better, with blocks

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  12. 12
    DataFairy113

    Generate real looking fake data for your tests and demos

    2018

  13. 13DD

    Gleb, Alex, Erez and Simon here – we are building an open-source tool for comparing data within and across databases at any scale. The repo is at https://github.com/datafold/data-diff, and our home page is https://datafold.com/. As a company, Datafold builds tools for data engineers to automate the most tedious and error-prone tasks falling through the cracks of the modern data stack, such as data testing and lineage. We launched two years ago with a tool for regression-testing changes to ETL code…

    2022

  14. 14

    A diagramming tool for systems, like software architecture

    2020

  15. 15DA

    Dear HN, I am Riwaj, the cofounder of dstack.ai (https://github.com/dstackai). A few months ago, we built an online service that allows users to publish data visualizations from Python or R. The idea was to build a tool that did not require additional programming or front-end development for publishing data visualizations. Such a code can be invoked from either Jupyter notebook, RMarkdown, Python, or R scripts. Once the data is pushed, it can be accessed via a browser. Open-sourcing dstack: During our customer discovery phase, we realized that dstack.ai should integrate a lot…

    2020

  16. 16

    Generate realistic, randomized data in over 30 languages

    2023

  17. 17

    Generate beautiful, typesafe code from data

    2018

  18. 18

    Search, visualize and analyze spatial and unstructured data

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  19. 19SN

    Hello. Briefly about Structpad: All interaction with app comes down to simple typing, like in a notepad. No buttons, commands or special characters needed. However, you can still build complex structured data. Something about why I'm building Structpad: I love taking notes and I think it's necessary for deep thinking because our brain is very powerful, but it has one weakness - memory. I noticed that not only the text itself matters, but also some invisible structure in our minds. There are various tools that try to reveal this structure, such as filenames, folders, tags, links, tables of…

    2022 · structpad.app

  20. 20

    Figma plugin to generate & customise random data for designs

    2022

  21. 21AC

    I always strive to write better, clean and readable code. But I often find unit tests are hard to read, and especially harder to quickly identify what are the important pieces, or even what the test is testing about. So I came up with this lightweight library to help enforce unit tests with a Given-When-Then structure. I hope you find this useful. Any feedback are welcome. https://github.com/cobrakai-lab/Cobrakai.GWTUnit

    2021

  22. 22RB
  23. 23SG

    Scaling data teams today means dealing with the complexity of the modern data stack. While DBT has become a core tool for transforming raw data into structured, analytics-ready tables, most teams are using it in ways that lead to chaos: duplicated models, inconsistent metrics, and inefficient SQL that directly impacts cloud spend. The real issue isn’t with DBT itself—it’s in how it’s applied across teams. Here’s the typical setup: Finance defines a revenue model, Marketing calculates customer lifetime value, and Product defines churn. All in DBT, but all with slightly different logic,…

    2024 · github.com

  24. 24DI

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