SDV Enterprise

Overview

SDV Enterprise is a Python SDK for creating synthetic structured data for software testing, machine-learning development and related work. It is best suited to teams that need to model connected database tables and keep data processing within their own environment. Its main trade-off is a paid, usage-billed path to broader capabilities; a free Community plan provides a narrower starting point.

Key features

The SDK generates data in the same general properties and formats as real data, working with rows and columns in database tables, CSV, Excel and JSON. It supports single-table, multi-table and sequential data. Its ability to learn relationships across complex multi-table schemas is particularly useful when test data must preserve links between tables rather than producing isolated records.

Users can select from hundreds of data-processing options, anonymize sensitive personal information and provide business logic to guide the AI model. The downloadable SDK runs on Linux, Windows and macOS in a secure or on-premises environment, without requiring GPUs. DataCebo says customer data and generated models remain in that environment and are not hosted, stored or accessed by the company. Telemetry may still transmit usage and diagnostic information—including sampled cell counts, performance data, error logs and crash reports—though it excludes customer data and created models.

AI Connectors can detect database metadata, import training-data subsamples and export synthetic data in the original database format. Supported connectors are AlloyDB, BigQuery, MSSQL, Oracle, PostgreSQL and Spanner. This can reduce manual movement between a database and a synthetic-data workflow, but connectors are an add-on for the Enterprise Base plan and are included in Bundles.

Pricing

SDV Community costs 0.00 USD per free, with no-cost billing. It includes five data types, five basic constraints, nine models, CSV and Excel support, and forum support. That is a practical way to begin or handle narrower file-based work, but the listed model and data-type counts are well below Enterprise Base's 12+ models and 10+ data types; AI Connectors are not part of this plan.

SDV Bundles costs 250.00 USD per month, billed per bundle per user plus usage. It includes CAG, XSynthesizers, Targeted Sampling, Differential Privacy and AI Connectors. It suits users seeking those named capabilities and database workflows, though the per-user and usage charges mean the monthly amount is not the full cost for a team generating data.

SDV Enterprise Base costs 500.00 USD per month, billed per user plus usage. It includes 12+ models, 10+ data types and dedicated forum support; AI Connectors are an add-on. Pay-as-you-go charges apply to synthetic data created, and a spending cap can help control monthly usage costs. Support also includes commercially reasonable efforts to answer up to 10 inquiries per month within 2 to 3 business days. There is no free trial, so the Community plan is the available no-cost way to assess a limited version before committing.

Platforms

SDV Enterprise supports Linux, Windows and macOS with specified 64-bit Python and pip requirements. Its self-hosted deployment is the relevant option for teams that need processing to stay in a secure or on-premises environment; GPU hardware is not required.

Who it's for

Choose SDV Enterprise when synthetic data must retain structure across related tables, when teams need database connectors, or when deployment boundaries matter. The Community plan is a sensible starting point for basic CSV and Excel work. Teams needing the paid models, broader data-type support or connector workflows should budget for per-user fees and usage charges. It is less compelling for a reader who only needs a free, narrowly capped generator or who does not need structured, multi-table data.

Pros and cons

• Pro: Multi-table modeling can preserve intertable patterns, a meaningful advantage for realistic testing of relational schemas.
• Pro: Self-hosted operation keeps customer data and models in the customer environment, and does not require GPUs.
• Pro: Database connectors support importing subsamples and exporting in the original database format.
• Con: Enterprise costs combine per-user pricing with usage billing, so spend grows with team size and generated data.
• Con: Community is limited to five data types, five basic constraints and nine models, with only CSV and Excel support.
• Con: Diagnostic telemetry may include usage patterns, performance data, logs and crash reports, even though customer data and created models are excluded.

Alternatives

Browse the Synthetic Data Generation Software category to compare products in this field.

Synth Studio is a better fit for a reader seeking a free option with a stated limit of up to 1M rows per generation and an MIT License.

YData SDK may suit teams that want a free monthly-credit plan with all features and 20+ connectors, or pay-as-you-go pricing starting at 1.00 USD per onc.

NVIDIA ShadowPlay is another listed alternative.

Tonic.ai offers a freemium option and a Fabricate Plus plan at 29.00 USD per month, billed at $29 per month, with $25 of monthly credits and pay-as-you-go additional usage.

Simudyne Pulse is another freemium alternative.

SynthCity is a free, open-source Python library for Linux, installable from PyPI or source, and may suit developers seeking that format.

Synthesized is a freemium alternative with pricing available by contacting sales to book a demo.

Verdict

SDV Enterprise is the stronger fit for teams that need structured synthetic data across related tables, database integrations and self-hosted control. Those capabilities justify considering it when preserving data relationships and keeping customer data in-house matter more than a simple low-cost start. Choose another tool if you need a genuinely free workflow beyond Community's narrow limits or want to avoid per-user and usage charges.