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DDL to Data
Mockaroo
Generate Data
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Random Data
TestDataHub
DDL to Data is a developer tool that automatically generates realistic test data from SQL schemas. Simply paste your CREATE TABLE statement and get back JSON data with smart type detectionโcolumn names like "email" produce real email formats, "phone" produces phone numbers, etc. It supports PostgreSQL, MySQL, and SQLite, handles foreign key relationships for referentially-intact data, and integrates easily into CI/CD pipelines via REST API. Ideal for database testing, seeding dev environments, creating demo data, and automated test pipelines.
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DDL to Data's answer:
No LLM, no prompts, no AI costs. DDL to Data uses deterministic pattern-matching โ not machine learning โ to generate realistic test data from your SQL schema in milliseconds. It's fast, predictable, and won't hallucinate. Column named "email" produces an email, "phone" produces a phone number. Same schema, same structure, every time. Plus it handles foreign key relationships to generate referentially-intact data across multiple tables.
DDL to Data's answer:
Unlike AI-powered tools, DDL to Data has zero token costs, sub-second response times, and deterministic output, critical for CI/CD pipelines. Unlike Faker libraries, it requires zero configuration: paste your CREATE TABLE and get intelligent, type-aware data without writing any setup code. It also supports multiple output formats (JSON, CSV, SQL, Parquet, Excel) and can seed data directly into your PostgreSQL database.
DDL to Data's answer:
Backend developers, QA engineers, and DevOps teams who need realistic test data for database testing, seeding dev environments, CI/CD pipelines, and product demos. Particularly useful for teams who want a reliable, no-config utility that just works, without adding AI dependencies to their infrastructure.
DDL to Data's answer:
Every new project meant the same tedious ritual: write the schema, then manually create arrays of fake emails, phone numbers, and timestamps. Over and over. It struck me that the schema already contains everything needed to generate realistic data, column names are semantic. "email" means email, "created_at" means timestamp. So I built an API that does the obvious thing automatically, without any AI complexity
DDL to Data's answer:
FastAPI (Python) backend with PostgreSQL and SQLAlchemy. Next.js 14 frontend with TypeScript and Tailwind CSS. Hosted on AWS with Docker containers, and CircleCI for CI/CD.
DDL to Data's answer:
Currently in public beta and growing organically. Early adopters include indie developers and small engineering teams using it for local development and automated testing pipelines.
Based on our record, GitHub Desktop seems to be more popular. It has been mentiond 136 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Optional: You can also download GitHub Desktop (https://desktop.github.com) if you prefer a GUI version, but this guide focuses on Git Bash to understand the basics. - Source: dev.to / 7 months ago
Download the latest version from the GitHub Desktop website. - Source: dev.to / over 1 year ago
Iโm not going to dive into Git commands here โ you can find plenty of tutorials online. If youโre not a fan of using the plain terminal CLI, you can also manage repositories with tools like GitHub Desktop or SourceTree, which provide a more visual, intuitive interface. - Source: dev.to / almost 2 years ago
Using terminal commands isnโt necessary for basic adoption of Git with Corticon Studio files, though. There are various tools that will allow us to bypass the command line when defining rules, including the built-in Eclipse plugin for Git version control. If youโll be storing your assets on GitHub, though, an even easier solution is GitHub Desktop, a free desktop software that GitHub offers. It can be used in... - Source: dev.to / almost 2 years ago
Nix currently is akin to git's "porcelain": powerful but esoteric. However, much like git evolved into exoteric, user-friendly tools such as git-flow, GitHub Desktop, and Tower to become user-friendly, many developers are building abstractions, wrappers, and utilities to simplify Nix usage. Let's briefly look at a few of these tools now. - Source: dev.to / about 2 years ago
GitKraken - The intuitive, fast, and beautiful cross-platform Git client.
Mockaroo - A realistic data generator to test your app
SourceTree - Mac and Windows client for Mercurial and Git.
Generate Data - GenerateData.com: free, GNU-licensed, random custom data generator for testing software
SmartGit - SmartGit is a front-end for the distributed version control system Git and runs on Windows, Mac OS...
Snaplet - Snaplet gives developers production-accurate data and preview databases they can code against, so they can focus on shipping. Ditch the seed script forever!