Mage Data vs Protegrity Comparison: Reviews, Features, Pricing & Alternatives in 2026

Mage Data helps you secure your most sensitive information by providing a unified platform for data discovery and protection. You can automatically scan your entire data estate—including databases, cloud storage, and big data environments—to identify where sensitive data lives. Once discovered, the platform allows you to apply sophisticated security measures like static and dynamic data masking to keep your information safe from unauthorized access.

The platform is designed for mid-to-large enterprises and organizations in highly regulated industries like finance and healthcare. You can simplify your compliance journey for regulations like GDPR, CCPA, and HIPAA by maintaining a clear inventory of your data and enforcing consistent security policies. By automating these complex processes, you reduce the risk of data breaches while ensuring your teams have the data they need to stay productive.

Protegrity helps you secure your most sensitive data across complex environments without slowing down your business operations. You can protect information at the rest, in transit, or in use by applying fine-grained security policies that follow the data wherever it moves. Whether you are managing data in Snowflake, AWS, or on-premises servers, you maintain full control over who sees what through advanced tokenization and anonymization techniques.

The platform solves the conflict between data utility and data privacy by allowing your teams to run analytics on protected data. You can meet strict global compliance requirements like GDPR and PCI DSS while still gaining insights from your information. It is designed for large-scale enterprises in highly regulated sectors like banking, healthcare, and retail that need to balance rigorous security with high-speed data processing.

• Sensitive Data Discovery Scan your structured and unstructured data sources automatically to find PII, PHI, and PCI data without manual effort.
• Data Classification Organize your discovered data into clear categories so you can apply the right security policies based on risk levels.
• Static Data Masking Create realistic but non-sensitive versions of your production data for use in testing, development, and analytics environments.
• Dynamic Data Masking Protect sensitive information in real-time by masking data as it is accessed, ensuring users only see what they need.
• Data Privacy Vault Isolate and tokenize your most sensitive data elements in a secure vault to minimize your overall attack surface.
• Compliance Reporting Generate detailed audit reports to demonstrate compliance with global privacy regulations like GDPR and CCPA to your stakeholders.

• Vaultless Tokenization. Protect your sensitive data by replacing it with random tokens that maintain original formats without the latency of a database.
• Dynamic Data Masking. Control visibility in real-time by masking sensitive information based on the specific role and permissions of the person viewing it.
• Centralized Policy Management. Define your security rules once in a single interface and automatically apply them across all your cloud and local platforms.
• Cloud Security Gateways. Secure your data before it ever reaches the cloud, ensuring you stay in control of your encryption keys and privacy.
• Privacy Analytics Support. Run complex queries and AI models on protected data so your researchers get insights without seeing actual personal information.
• Format-Preserving Encryption. Encrypt your data while keeping its original length and character type to avoid breaking your existing applications or databases.