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Alternatives

Products that do what judgedata does

Generate test cases and datasets for competitive programming

  1. 1

    Generate custom data & API to build apps in less than 30s

    2021

  2. 2

    First AI agent automating entire software testing process

    2025 · testsprite.com

  3. 3GT

    2013 · databasetestdata.com

  4. 4
    Xata236

    The data platform for modern web applications

    2022

  5. 5MS

    Hey HN, I’m the author. I built Misata because existing tools (Faker, Mimesis) are great for random rows but terrible for relational or temporal integrity. I needed to generate data for a dashboard where "Timesheets" must happen after "Project Start Date," and I wanted to define these rules via natural language. How it works: LLM Layer: Uses Groq/Llama-3.3 to parse a "story" into a JSON schema constraint config. Simulation Layer: Uses Vectorized NumPy (no loops) to generate data. It builds a DAG of tables to ensure parent rows exist before child rows (referential integrity).…

    Dec 2025 · github.com

  6. 6

    Two weeks ago I was on my babymoon in Corfu, Greece. While in transit, I was overseeing a GSoC intern submit an important feature to my array database library, Xarray-SQL. He added `to_dataset()`, which completed the roundtrip between thinking of array data in a tabular model simultaneously as gridded rasters (the premise of the project is that every Nd array can be mapped to 2d, where orthogonal dims of the Nd array are just primary keys of a tabular representation). We discussed in chat, now that this feature existed, what demos could we make that would prove this data model works? With…

    Jul 2026 · github.com

  7. 7
    Quizgecko147

    Generate quiz questions using AI

    2022

  8. 8

    Connect DecisionBox to your Databricks to validate findings

    May 2026 · decisionbox.io

  9. 9GQ

    One of the coolest things I've been able to get GPT-3 to do is generate questions based on a piece of text. So, I built a simple site to help others do the same. Hopefully, this can be useful to teachers, trainers, or just anyone who wants to create a fun and unique quiz.

    2022 · quizgecko.com

  10. 10

    An open benchmark for AI agents that test APIs

    May 2026 · resources.kusho.ai

  11. 11GJ
  12. 12

    Create mock and sample JSON using a powerful template syntax

    2014

  13. 13

    Figma plugin to generate & customise random data for designs

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  14. 14

    Curated collection of A/B test results

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  15. 15

    Generate 1M+ rows of SQL/Mongo data instantly & fast.

    Jan 2026

  16. 16KA

    I built this because Cursor, Claude Code and other agentic AI tools kept giving me tests that looked fine but failed when I ran them. Or worse - I'd ask the agent to run them and it would start looping: fix tests, those fail, then it starts "fixing" my code so tests pass, or just deletes assertions so they "pass". Out of that frustration I built KeelTest - a VS Code extension that generates pytest tests and executes them, got hooked and decided to push this project forward... When tests fail, it tries to figure out why: - Generation error: Attemps to fix it automatically, then tries again -…

    Jan 2026 · keelcode.dev

  17. 17DT

    I built DDL to Data after repeatedly pushing back on "just use production data and mask it" requests. Teams needed populated databases for testing, but pulling prod meant security reviews, PII scrubbing, and DevOps tickets. Hand-written seed scripts were the alternative slow, fragile, and out of sync the moment schemas changed. Paste your CREATE TABLE statements, get realistic test data back. It parses your schema, preserves foreign key relationships, and generates data that looks real, emails look like emails, timestamps are reasonable, uniqueness constraints are honored. No setup, no…

    Jan 2026

  18. 18

    Synthetic Test Data Generator

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  19. 19WA
  20. 20VU

    Visions is a python library for working with user defined data type systems. Out of the box, it provides type inference and automated data cleaning of sequence data with backend specific implementations for pandas, spark, python, and numpy. We often use it as a first pass cleaning step when working with tabular data and to simplify the backend logic of both pandas-profiling[1] and our tabular data compression library compressio[2]. Because data types are user defined, we can build user customizable libraries based around types without adding code complexity. In the case of compressio that…

    2022 · github.com

  21. 21WA
  22. 22IM
  23. 23

    Generate Realistic Test Data — Instantly.

    Nov 2025

  24. 24ST

    Hi HN — we've built a testing framework for Supabase that spins up fast, isolated Postgres databases for each test case. It’s designed to make RLS policies easy to validate with real database state, without global test fixtures or mock auth. Features: - Instant isolated Postgres DBs per test - Automatic rollback after each test - RLS-native testing with `.setContext()` for auth simulation - Flexible seeding (SQL, CSV, JSON, JS) - Works with Jest, Mocha, and any async test runner - CI-friendly (runs cleanly in GitHub Actions) We also published example projects and a free set of tutorials:…

    Nov 2025 · npmjs.com

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