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DataSynthesizer
What it is
DataSynthesizer is an open-source tool for generating synthetic data that simulates a supplied dataset. The project describes its approach as applying differential privacy techniques to provide a strong privacy guarantee. Its demonstrations cover random, independent-attribute, and correlated-attribute modes. The documented input must be a table in first normal form. To use it, install the package with `pip install DataSynthesizer`, run example notebooks in Jupyter Notebook, or start the included Django project locally and open its web interface in a browser at `/synthesizer`. The project identifies Python pip, Jupyter Notebook, and the companion Django interface as its integrations. It aims to support collaboration between data scientists and owners of sensitive data. DataSynthesizer is free and MIT-licensed, with self-hosted and web platforms listed. GitHub Issues are available for project questions and reports. Its stated scope excludes relational and unstructured data.
For and against
For
- Free and MIT-licensed.
- Offers three demonstrated synthesis modes.
- Includes a locally run Django web interface.
- Documents Jupyter Notebook examples.
- Project describes differential privacy techniques.
Against
- Input must be a first-normal-form table.
- Does not cover relational or unstructured data.
- No free trial is listed.
The verdict
DataSynthesizer provides several documented ways to generate synthetic data, including notebook and local web-interface workflows. Its input requirement and stated scope make the supported data structure important to check first.
Who it suits
It suits data scientists and owners of sensitive data who need to collaborate on synthetic data from a first-normal-form table. Users comfortable with Python, Jupyter Notebook, or a locally run web interface can use its documented workflows.
Plans and prices
DataSynthesizer
MIT-licensed software · install with pip · input must be a first-normal-form table
Read 4 Oct 2026 · github.com
On the record
- Input requirement
- The documented input assumption is that the dataset is a table in first normal form.github.com · read 4 Oct 2026
- Installation
- The README gives `pip install DataSynthesizer` as the installation command.github.com · read 4 Oct 2026
- Integration
- The published usage instructions identify Python pip, Jupyter Notebook, and the companion Django web UI.github.com · read 4 Oct 2026
- Intended users
- The project says it aims to facilitate collaboration between data scientists and owners of sensitive data.github.com · read 4 Oct 2026
- License
- The repository identifies its license as MIT.github.com · read 4 Oct 2026
- Local web UI
- A Django project includes a web UI that can be run locally and opened in a browser at `/synthesizer`.github.com · read 4 Oct 2026
- Maker identity
- The GitHub organization describes Data, Responsibly as a responsible data management platform and tools project and links to dataresponsibly.org.github.com · read 4 Oct 2026
- Modes
- The repository includes demos for random, independent-attribute, and correlated-attribute modes.github.com · read 4 Oct 2026
- Notebook use
- The README directs users to run example notebooks with Jupyter Notebook.github.com · read 4 Oct 2026
- Privacy
- The project says it applies differential privacy techniques to provide a strong privacy guarantee.github.com · read 4 Oct 2026
- Purpose
- DataSynthesizer generates synthetic data that simulates a given dataset.github.com · read 4 Oct 2026
- Support
- The repository exposes GitHub Issues for project questions and reports.github.com · read 4 Oct 2026
