Contact for pricing🇦🇺
Listed Sydney-based provider of AI training data, RLHF, speech and multimodal data, with the ADAP platform and a global contributor network.
SDV (Synthetic Data Vault) overview and key facts (October 2026)
Python library from DataCebo for generating synthetic tabular and relational data with generative models.
Free
from $500 per month
What is SDV (Synthetic Data Vault)?
SDV (Synthetic Data Vault) is a Python library for data scientists who need synthetic versions of single tables or whole relational databases for testing, sharing or model training.
SDV is developed by DataCebo, which also maintains SDMetrics for evaluation and SDGym for benchmarking. The GitHub repository had about 3,600 stars with commits on September 28, 2026, and DataCebo reports more than 18 million downloads of SDV Community. The community version includes nine models and basic constraints and is licensed under the Business Source License, which limits commercial use. SDV Enterprise adds more models, data types and support, and runs within the customer's security boundary.
SDV (Synthetic Data Vault) AI features and use cases
- Synthesizes whole databasesMulti-table synthesizers learn relationships between tables and produce a synthetic database with consistent keys. Developers get realistic test data without copying production.
- Respects business rulesConstraints keep generated values within valid ranges and logical combinations. Test data stays usable for applications that check such rules.
- Measures quality and privacySDMetrics compares synthetic and real data on statistical similarity and privacy risk. Teams can document whether the synthetic set is fit for its purpose.
What sets SDV (Synthetic Data Vault) apart
- Covers relational data across several linked tables.
- Community version under the Business Source License, commercial Enterprise edition with usage-based pricing and spending cap.
Where SDV (Synthetic Data Vault) is strongest
Available internationally
SDV is a Python library used worldwide; DataCebo reports more than 18 million downloads of the community version.
Questions to ask before you buy SDV (Synthetic Data Vault)
Check the Business Source License terms before commercial use of SDV Community, since commercial use is limited. Running SDV locally keeps data in your environment, but your team maintains the Python stack. Have privacy experts review whether synthetic output derived from personal data is anonymous for your purpose.
SDV (Synthetic Data Vault) reviews
No reviews yet. Be the first to share how your team uses it.
Every review shows its verification level. We read each one before it goes live. How we check reviews
Questions about SDV (Synthetic Data Vault)
Is SDV free for companies?
SDV Community is free but licensed under the Business Source License with limited commercial use. SDV Enterprise starts at $500 per month plus usage.
Who maintains SDV?
DataCebo develops SDV together with SDMetrics and SDGym.
Can SDV handle several linked tables?
Yes. SDV includes synthesizers for relational data that keep relationships between tables.
SDV (Synthetic Data Vault) update historyno updates yet
No changes recorded for SDV (Synthetic Data Vault) yet.
Changes the vendor made and confirmed user reports, each checked against the vendor's own pages. We review every tool monthly.
Alternatives to SDV (Synthetic Data Vault)
Tools in the same category (Synthetic data) with the most overlapping markets.
Contact for pricing🇦🇹
Platform and open-source SDK from Vienna for synthetic tabular data with differential privacy and an AI assistant for data analysis.
Flat fee🇳🇱
Amsterdam-based platform for synthetic test data with AI generation, masking and a sensitivity scanner, deployed in the customer's environment.
Free🇺🇸
Instruction-tuning mix of 939,344 examples from the Allen Institute for AI, used to train the Tulu 3 models.
Compare SDV (Synthetic Data Vault) with these alternatives →