Column-Level Data Masking Across Multiple Database Engines

Cross-Platform Third-Party Solutions

Several enterprise vendors offer database-agnostic solutions that support column-level masking across multiple database platforms. Informatica Data Privacy Management stands out with extensive platform coverage including Oracle, SQL Server, MySQL, PostgreSQL, DB2, Teradata, Sybase, MongoDB, Cassandra, Snowflake, Redshift, and BigQuery. The solution provides static, dynamic, and on-the-fly masking capabilities with format-preserving encryption and AES-256 encryption, implementing policy-based controls by role and user across on-premises, cloud, and hybrid deployments. Delphix Dynamic Data Platform offers similar multi-platform support with a distinctive capability for synthetic data generation alongside traditional static and dynamic masking. The platform supports environment-based masking policies with AES-256 encryption and tokenization, available through on-premises, cloud, and SaaS deployment models. Imperva Data Security Fabric extends protection to big data platforms including Hadoop while providing real-time masking capabilities. The solution employs format-preserving encryption, AES-256, and tokenization with user and role-based policies across deployment environments. Protegrity Data Protection Platform distinguishes itself with vaultless tokenization technology, eliminating the need for token vaults while maintaining format-preserving encryption. The platform implements fine-grained access controls across traditional databases and modern data warehouses like Snowflake. Baffle Data Protection Service takes a cloud-native approach with application-layer masking and always-encrypted architecture using a proxy-based model. The solution works transparently between applications and databases including MySQL, PostgreSQL, MongoDB, Snowflake, Redshift, and BigQuery without requiring application code modifications. Baffle DPS implements a three-component architecture with Baffle Manager for management, Baffle Shield as the proxy layer, and key virtualization, supporting both Bring Your Own Key and Hold Your Own Key models.

Native Column-Level Encryption Capabilities

Each major database platform provides native functions for column-level encryption, though implementation requires query and application modifications. Aurora MySQL offers AES_ENCRYPT and AES_DECRYPT functions recommended for use with initialization vectors and SHA2 for enhanced security. SQL Server provides ENCRYPTBYKEY and DECRYPTBYKEY functions along with the Always Encrypted feature for cell-level encryption. Aurora PostgreSQL delivers encryption capabilities through the pgcrypto extension with pgp_sym_encrypt, pgp_sym_decrypt, and standard encrypt and decrypt functions supporting AES encryption.

Standardized Implementation Approach

For organizations seeking a consistent approach across multiple database platforms with minimal database-layer modifications, implementing encryption at the application layer provides the most standardized solution. The AWS Encryption SDK delivers a unified encryption library with built-in AWS KMS integration for centralized key management. This approach allows database schemas to store encrypted data as binary or text fields with consistent handling across all platforms while maintaining security through AWS KMS for encryption key management integrated with all AWS services.

Sources: How to Tokenize and De-identify Your Data in Amazon RDS with Baffle

How to Encrypt Database Columns with No Impact on Your Application Using AWS DMS and Baffle