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DataSynthesizer

github.com

Free plan WebSelf-hosted
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Spec score 7.8 #12 of 25 in AI Synthetic Data Generators

What it is

DataSynthesizer generates synthetic data that imitates a supplied dataset while applying differential privacy techniques, according to the project. Its demonstrations cover random, independent-attribute, and correlated-attribute modes. The documented input must be a table in first normal form, and the project states that relational and unstructured data are outside its scope. Installation uses the Python command `pip install DataSynthesizer`. Users can run example notebooks with Jupyter Notebook or start the included Django project locally and open its web interface at `/synthesizer`. The project is MIT-licensed and offers GitHub Issues for questions and reports. It is intended to help data scientists work with owners of sensitive data. DataSynthesizer is free and open source, with self-hosted and web platforms listed. Its documented integrations are Python pip, Jupyter Notebook, and the companion Django interface. There is no free trial because the project lists only a free plan.

Spec sheet

Purpose
DataSynthesizer generates synthetic data that simulates a given dataset.Read 4 Oct 2026 · github.com
Intended users
The project says it aims to facilitate collaboration between data scientists and owners of sensitive data.Read 4 Oct 2026 · github.com
Privacy
The project says it applies differential privacy techniques to provide a strong privacy guarantee.Read 4 Oct 2026 · github.com
Support
The repository exposes GitHub Issues for project questions and reports.Read 4 Oct 2026 · github.com
License
The repository identifies its license as MIT.Read 4 Oct 2026 · github.com
Input requirement
The documented input assumption is that the dataset is a table in first normal form.Read 4 Oct 2026 · github.com
Installation
The README gives `pip install DataSynthesizer` as the installation command.Read 4 Oct 2026 · github.com
Integration
The published usage instructions identify Python pip, Jupyter Notebook, and the companion Django web UI.Read 4 Oct 2026 · github.com
Local web UI
A Django project includes a web UI that can be run locally and opened in a browser at `/synthesizer`.Read 4 Oct 2026 · github.com
Maker identity
The GitHub organization describes Data, Responsibly as a responsible data management platform and tools project and links to dataresponsibly.org.Read 4 Oct 2026 · github.com
Modes
The repository includes demos for random, independent-attribute, and correlated-attribute modes.Read 4 Oct 2026 · github.com
Notebook use
The README directs users to run example notebooks with Jupyter Notebook.Read 4 Oct 2026 · github.com

Plans and prices

DataSynthesizer Free MIT-licensed software · install with pip · input must be a first-normal-form table Read 4 Oct 2026 · github.com

Every DataSynthesizer plan and price →

Strong points and limits

Strong points

  • Uses differential privacy techniques
  • Provides three documented synthesis modes
  • MIT-licensed and free to use
  • Includes Python, Jupyter, and Django routes
  • Can run self-hosted

Limits

  • Input must be a first-normal-form table
  • Does not cover relational data
  • Does not cover unstructured data
  • No free trial is listed

Who it suits

DataSynthesizer suits data scientists and teams collaborating around sensitive information who need synthetic tabular data. It is aimed at users comfortable with Python, notebooks, or a locally run Django interface.

Verdict

DataSynthesizer is a focused, self-hosted option for producing synthetic tabular data through Python, notebooks, or a local web UI. Its first-normal-form requirement and lack of relational or unstructured-data support define its boundaries.

Where Specifiction places it

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