A powerful, Rust-based database anonymizer that generates native SQL dumps with flexible transformation rules.
Datanymizer is a database anonymization tool written in Rust that generates sanitized SQL dumps from production databases. It replaces sensitive data like names, emails, and phone numbers with realistic fake data using a flexible rule-based configuration, enabling safe use of production-like data in development and testing environments. The tool focuses on PostgreSQL support and produces native dumps that can be imported directly without extra tooling.
Developers, DevOps engineers, and QA teams who need to work with realistic but anonymized database copies for development, testing, or analytics without exposing sensitive user information.
Developers choose Datanymizer for its high performance due to being Rust-based, its extensive and flexible rule system for precise data transformations, and its ability to generate directly usable PostgreSQL dumps that maintain database integrity and relationships.
Powerful database anonymizer with flexible rules. Written in Rust.
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Written in Rust, Datanymizer delivers fast and reliable processing for large databases, minimizing overhead during dump generation.
Offers over 70 built-in rules like emails, phones, and dates via YAML config, enabling precise, column-level anonymization with realistic fake data.
Generates database-native SQL dumps that import directly with tools like psql, eliminating third-party dependencies and ensuring compatibility.
Maintains data relationships through cross-row references and a built-in key-value store, preserving consistency across tables in anonymized output.
Only supports PostgreSQL currently, with MySQL/MariaDB listed as TODO, making it ineffective for multi-database or heterogeneous environments.
The YAML rule system requires deep understanding of schema and transformers, with complex setups for templates, uniqueness, and conditions that can be error-prone.
Generates full SQL dumps only, lacking support for streaming changes or delta updates, which can be inefficient for frequently changing databases.