
GitHub
GitLab
BitBucket
openDesktop.org
Gitea
Launchpad.net
OSOR
The Complete Open-Source and Business Software Platform.

Mockaroo
Generate Data
Snaplet
Random Data
TestDataHub
Turn SQL schemas into realistic test data in seconds. Perfect for testing, demos, and development.

Which is more popular?
Website, pricing, platforms and company facts side by side.
|
|
|
|
|---|---|---|
| Website | sourceforge.net | ddltodata.com |
| Pricing | — | |
| Company | — | Startup from the United States · 2025 |
| Listed in |
In their own words, as submitted to SaaSHub.


No description of SourceForge yet.
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 detection—column names like "email" produce real email formats, "phone" produces phone numbers, etc. It supports...
What each product offers, as listed by its team.


Possible disadvantages
An editorial look at what each product does well and who it suits.


Overall verdict
Why this product is good
Recommended for
Overall verdict
Why this product is good
Recommended for
Walkthroughs and reviews on video.
Presearch Privacy Review #27 - Sourceforge
More videos
No DDL to Data videos yet. You could help us improve this page by suggesting one.
How often each product is chosen within a category, 0–100% relative to the other.


As answered by people managing SourceForge and DDL to Data.
DDL to Data's answer:
No LLM, no prompts, no AI costs. DDL to Data uses deterministic pattern-matching — not machine learning — 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.
Share your experience with using SourceForge and DDL to Data. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


SourceForge is a great place for people who like open-source software. It offers a strong platform where you can find, review, and handle software, all while helping the open-source community.
SourceForge’s user interface works fine, but it could do with a modern overhaul to make it easier on the eye and give it a more intuitive feel. While it has a large community, SourceForge’s support is not as extensive...
Sourceforge has been around longer than most, and it has the projects to prove it. Lots of open source Linux, Windows and Mac projects are hosted on SF. It has a totally different project structure when compared with...
We have no reviews of DDL to Data yet. Be the first one to post
When comparing SourceForge and DDL to Data, you can also consider the following products.

Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.
Compare GitHub to SourceForge or DDL to Data:
A realistic data generator to test your app
Compare Mockaroo to SourceForge or DDL to Data:

Create, review and deploy code together with GitLab open source git repo management software | GitLab
Compare GitLab to SourceForge or DDL to Data:

GenerateData.com: free, GNU-licensed, random custom data generator for testing software
Compare Generate Data to SourceForge or DDL to Data:

Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.
Compare BitBucket to SourceForge or DDL to Data:

Snaplet gives developers production-accurate data and preview databases they can code against, so they can focus on shipping. Ditch the seed script forever!
Compare Snaplet to SourceForge or DDL to Data: