Alternatives
Products that do what Faker Forge does
FakerForge — AI-Powered Dummy Data Generator
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2019 · github.com
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Hey HN, We just shipped a new AI-powered feature... BUT the "AI" piece is largely in the background. Instead of relying on a chatbot, we've integrated AI (with strict input & output guardrails) into a workflow to handle two specific tasks that would be difficult for traditional programming: 1. Identifying the most relevant base URL from HAR files, since it would be tedious to cover every edge case or scenario to omit analytics, tracking, and other network noise. 2. Generating synthetic data for API requests by passing the API context and faker-js functions to GPT-4. The steps are broken down…
2024 · docs.multiple.dev
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Hi, everyone! Lately, I've been working on quite a few applications that require a database, and as a result, I need some data to test everything. It has always taken me a lot of time to ask ChatGPT to generate fake data for me, so I decided to create a tool for developers called FakeData. FakeData allows developers to generate fake data easily with a simple UI/UX and customizable fields. This data can be used in their applications to test various functionalities. P.S. The app is not yet finished, and I would love to hear your honest feedback on it. Please be brutally honest about what…
2025 · fakedata-mu.vercel.app
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2017 · github.com
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I made an API mocking tool that imports a schema, populates fake data, then runs a local server. This is helpful for testing APIs or advanced prototyping. A demo video is here: https://www.loom.com/share/abad2cdf325e4e0b9addea1e14406166?... There’s two fun things about this tool 1. the complete lack of configs and schema annotations. i.e. you don’t need to learn faker-js. You just need your existing GraphQL schema and to to swap out the server URL in your frontend code. 2. the depth. Your fake objects have relationships to other fake objects. And in proxy mode, real…
2023 · github.com
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2025 · github.com
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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
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Hey HN! A few months ago we shared our AI dataset generator as an open source repo, and the response was incredible (https://news.ycombinator.com/item?id=44388093). We got requests from folks who wanted to use it without the hosting overhead, so we created both options: a hosted version (https://www.metabase.com/ai-data-generator for instant use and the source code fully open (https://github.com/metabase/dataset-generator) for anyone who wants to self-host or contribute. Looking forward to seeing how you use it and what you build on top of…
Sep 2025 · metabase.com
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