Synthetic Data Vault review
A broad Python-based toolkit for generating, evaluating, and exporting synthetic data.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Synthetic Data Vault is a Python library for generating and evaluating tabular synthetic data from real datasets. It supports single-table, sequential, and multi-table relational data, making it suitable for development teams that need programmatic control over synthetic datasets. The product works with CSV, Excel, pandas DataFrame, and JSON metadata, and supports on-premises deployment. Its free SDV Community plan includes five data types, five basic constraints, nine models, native CSV and Excel support, and community forum support.
Its main strength is breadth within an API-first workflow. Synthetic Data Vault combines generative AI synthesizers, constraint-based customization, statistical quality evaluation, visualization, conditional sampling, scalable sampling, and database import and export. The published database connectors include AlloyDB, BigQuery, MSSQL, Oracle, PostgreSQL, and Spanner. These capabilities make it a fit for teams working with relational structures or needing to compare generated data against source characteristics. SDV Enterprise Base adds 12+ models, 10+ data types, dedicated support, and access to AI Connectors as an add-on.
The plan structure also covers more specialized generation needs. SDV Bundles include Constraint Augmented Generation, XSynthesizers, Targeted Sampling, Differential Privacy, and AI Connectors, while Usage-Based Pricing charges for synthetic data created and includes a monthly spending cap. Teams should choose Synthetic Data Vault when API-based, self-hosted synthetic data generation and relational support matter more than a graphical platform. It is less suitable for buyers seeking broad platform coverage beyond an API or a packaged AI Connector experience without an add-on.
Synthetic Data Vault pros and cons
- Where it wins
- Supports single-table, sequential, and multi-table relational data
- Includes constraints, quality evaluation, visualization, and sampling
- Connects with AlloyDB, BigQuery, MSSQL, Oracle, PostgreSQL, and Spanner
- Where it doesn't
- Platform coverage is limited to API access
- AI Connectors are available only as an add-on
- Enterprise pricing includes additional usage charges
Synthetic Data Vault fact sheet, pricing and score →
Advertiser disclosure: iTechGuides is reader-supported. Vendors can pay for top positions in our rankings and for a place on other products' pages, and we may earn a commission when you click some links. Bought places stand at the number bought; this page and our disclosure say so. Paying vendors may get a fuller, more detailed review from our editors, and that review can change their score. How we rank.
Last updated · How we research and update