# A Comparison of SynDiffix Multi-table versus Single-table Synthetic Data

arXiv: https://arxiv.org/abs/2403.08463 · HTML: https://mlsanity.com/paper/2403.08463/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Mar 2024.

## Built on by (most cited first, 1 of 1)

- [Differentially Private Synthetic Data Generation for Relational Databases](https://mlsanity.com/paper/2405.18670/) (2024)

## Abstract (arXiv)

SynDiffix is a new open-source tool for structured data synthesis. It has anonymization features that allow it to generate multiple synthetic tables while maintaining strong anonymity. Compared to the more common single-table approach, multi-table leads to more accurate data, since only the features of interest for a given analysis need be synthesized. This paper compares SynDiffix with 15 other commercial and academic synthetic data techniques using the SDNIST analysis framework, modified by us to accommodate multi-table synthetic data. The results show that SynDiffix is many times more accurate than other approaches for low-dimension tables, but somewhat worse than the best single-table techniques for high-dimension tables.