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YData SDK
Seattle, USA
What it is
YData SDK is a Python toolkit for profiling data, improving it, and generating synthetic datasets. It creates automated profiles and comparison reports to help assess data quality and spot issues or drift. Synthetic data outputs include tabular, time-series, relational, text, Q&A, and document data. The documentation describes built-in PII detection and anonymization, as well as checks of generated data quality, utility, and privacy. Connectors include local files, cloud storage, databases, and Databricks; supported LLM backends include Workbench, OpenAI, Anthropic, and Gemini. The SDK supports Python 3.10 and later on Windows, Linux, and macOS. YData says its platform can run on customer cloud or on-premises infrastructure, avoiding data transfer between the customer and YData. The free plan lists all features and 20+ connectors. Pay-as-you-go costs $1.00 per credit; one credit covers 1 million data points or 10,000 tokens, with a 0.1-credit minimum transaction. Some features require native libraries installed before the SDK.
For and against
For
- Generates profiles and comparison reports
- Creates multiple types of synthetic data
- Includes PII detection and anonymization
- Supports Python 3.10 and later
- Can be deployed on customer cloud or on premises
Against
- Some features require prior native-library installation
- Requires Python 3.10 or later
The verdict
YData SDK combines profiling, synthetic-data generation, and privacy-related capabilities for Python workflows. Check native-library requirements for desired features before installing.
Who it suits
YData describes the SDK for data science, data engineering, analytics, and AI development teams. It suits Python users who need profiling or synthetic data across the listed data types.
Plans and prices
Free plan
Free monthly credit · all features available · 20+ connectors
Read 30 Sep 2026 · ydata.ai
Pay-as-you-go
1 credit per 1 million data points or 10,000 tokens · minimum transaction of 0.1 credits
Read 30 Sep 2026 · ydata.ai
Enterprise
All features available · predictable pricing
Read 30 Sep 2026 · ydata.ai
On the record
- Deployment
- YData says its platform can be deployed on customer cloud or on-premises infrastructure so data does not transfer between the customer and YData.ydata.ai · read 30 Sep 2026
- Integrations
- Documented connectors include local files, Amazon S3, Azure Blob Storage, Google Cloud Storage, BigQuery, Microsoft SQL Server, MySQL, Snowflake, and Databricks.docs.sdk.ydata.ai · read 30 Sep 2026
- Intended users
- YData describes the SDK as a Python toolkit for data science, data engineering, analytics, and AI development teams.pypi.org · read 30 Sep 2026
- LLM providers
- The SDK documentation names Workbench, OpenAI, Anthropic, and Gemini as supported LLM backends.docs.sdk.ydata.ai · read 30 Sep 2026
- Notable requirement
- The SDK installation guide says some features require native libraries to be installed before the SDK.docs.sdk.ydata.ai · read 30 Sep 2026
- Privacy features
- The SDK documentation describes built-in PII detection and anonymization alongside synthetic data generation.docs.sdk.ydata.ai · read 30 Sep 2026
- Profiling
- It generates automated data profiles and comparison reports to help evaluate data quality and detect issues or drift.ydata.ai · read 30 Sep 2026
- Purpose
- YData SDK is a Python toolkit for data profiling, data improvement, and synthetic data generation.docs.sdk.ydata.ai · read 30 Sep 2026
- Security
- YData states that it is a SOC 2 Type 2 certified company.ydata.ai · read 30 Sep 2026
- Support
- The SDK documentation directs users to contact YData for support and other inquiries.docs.sdk.ydata.ai · read 30 Sep 2026
- Supported platforms
- The SDK supports Python 3.10 and above and can be installed on Windows, Linux, or macOS.docs.sdk.ydata.ai · read 30 Sep 2026
- Synthetic data
- The SDK generates tabular, time-series, relational, text, Q&A, and document data.docs.sdk.ydata.ai · read 30 Sep 2026
- Synthetic data checks
- YData says it evaluates generated data quality, utility, and privacy using divergence and correlation measures, TSTR, and privacy tests such as inference attacks.ydata.ai · read 30 Sep 2026
