DUMMY DATABASE VS PlacePack.top

DUMMY DATABASE's answer

A free, all-in-one data generation platform that builds everything from simple tables to full relational databases with advanced controls, unique event sequences, ERD visualization, built-in SQL querying, and multiple export formats — no limits, no paywalls.

PlacePack.top's answer:

Most placeholder image tools give you one image at a time with no context about what it represents. PlacePack is built around bulk generation: you paste a full list of dimensions, name each one with an alias like hero:1600x900 or avatar:200x200, and download the entire set as a ZIP in one click. The images are deterministic, they never change between renders, which makes them safe to commit to a repository and use in automated tests, Storybook stories, and CI/CD pipelines. The REST API extends this to programmatic workflows: a single curl command can generate a full fixture set without any binary files in source control.

DUMMY DATABASE's answer

Unlike other data generators, DUMMY DATABASE gives you full relational database creation, unique event simulations, advanced control over every field, built-in SQL querying, and generous free limits — so you can go from idea to test-ready data without restrictions, subscriptions, or hidden fees

PlacePack.top's answer:

Lorem Picsum and similar services return random photos that change on every request, which is fine for quick mockups but unusable for visual regression testing or anything that needs a stable baseline. Placeholder.com generates images server-side with no bulk workflow, no ZIP download, and no API for programmatic use. PlacePack covers all three gaps: bulk generation, deterministic output, and a REST API. It also goes further with per-size color overrides, retina multipliers, 16 size presets for common platforms (Instagram, YouTube, email, responsive breakpoints), and shareable configuration URLs. Everything runs in the browser with no account required.

DUMMY DATABASE's answer

• Developers needing dummy databases for prototyping & testing.
• Analysts and BI specialists preparing demo dashboards.
• QA engineers creating data scenarios for testing.
• SQL learners who want practice datasets on demand.

PlacePack.top's answer:

Front-end developers and designers who need placeholder images that behave predictably in automated environments. The core users are developers building component libraries in Storybook (where Lorem Picsum causes flaky Chromatic runs), QA engineers setting up visual regression baselines in Playwright or Cypress, and designers filling Figma mockups with correctly-sized, on-brand placeholders before real assets arrive. A secondary audience is DevOps engineers who want to generate test fixture images in CI pipelines without committing binary files to the repository.

DUMMY DATABASE's answer

Began as a project for myself to be able to have custom datasets for testing purpose I've decided that it could be useful for wider audience and finalized it as a full-stack web project

PlacePack.top's answer:

PlacePack started as a fix for a specific frustration: a Storybook setup where components fetched images from Lorem Picsum, causing every Chromatic visual regression run to fail because the images changed. The existing options (random photo services, grey rectangle generators, committing stock photos) all had deal-breaking limitations. The first version was a quick browser tool that generated a ZIP of labeled SVG placeholders from a list of dimensions. It grew from there into a full generator with color theming, presets for common platforms, a REST API, and support for PNG and WebP in addition to SVG.

DUMMY DATABASE's answer

Python, Flask, HTML, CSS, Bootstrap, Redis, PostgreSQL, JavaScript

PlacePack.top's answer:

React and Vite for the browser-based generator (TypeScript, Tailwind CSS). PNG generation uses the HTML Canvas API on the main thread since Web Workers don't support SVG rasterization, so rasterization stays on the main thread with yielding between items to keep the UI responsive. SVG generation is pure string templating with no external dependencies. The REST API runs on Hono deployed as Vercel serverless functions, with Upstash Redis for rate limiting. WebP is generated via canvas.toBlob. The entire app is pre-rendered to static HTML at build time using renderToStaticMarkup + esbuild for SEO.

PlacePack.top's answer:

PlacePack is free and doesn't require an account, so there's no customer database. It's used by individual developers, designers, and QA engineers at companies of all sizes, primarily people who find it through searches like "storybook placeholder images", "visual regression test fixtures", or "placeholder image API". If you're using it at your company, we'd love to hear about it.