StreamGen vs Synthetic Data Vault

StreamGen has no write-up on Specifiction yet; its figures are above.

Synthetic Data Vault (SDV) is a Python library and software platform for creating synthetic data from real data. It supports single-table, sequential, and relational multi-table datasets. Users train synthesizers with different AI algorithms, generate data on demand, and evaluate quality with diagnostic and comparison tools. Constraints, preprocessing adjustments, and anonymization options provide additional control. SDV Community is an on-premises Python SDK developed on Python 3.9–3.14. Its free plan includes five data types, five basic constraints, nine models, CSV and Excel support, local file types, forum support, and limited commercial use. AI Connectors provide database metadata detection, data subsampling, and export in the original database format, with listed connectors for AlloyDB, BigQuery, MSSQL, Oracle, PostgreSQL, and Spanner. Differential Privacy uses an ε privacy-loss budget to balance privacy and quality. Paid options are SDV Bundles at $250 a month per bundle plus usage per user, and Enterprise Base at $500 a month plus usage per user.