Protegrity
Data de-identification tools
Sensitive data discovery software
Cloud data security software
Encryption software
Database security software
Data masking software
Cloud security software
Confidentiality software
Data security software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
Take the quiz to check if Protegrity and its alternatives fit your requirements.
Contact the product provider
Free Trial unavailable
Free version
Small
Medium
Large
-
What is Protegrity
Protegrity is a data security platform focused on protecting sensitive data across databases, applications, and cloud data environments using tokenization, encryption, and data masking. It is used by security, privacy, and data governance teams to reduce exposure of regulated data (for example, payment and personal data) while maintaining usability for analytics and operational systems. The product commonly integrates with enterprise data stores and pipelines to apply protection policies consistently across environments. It also supports discovery and classification workflows to help identify where sensitive data resides before applying controls.
Strong tokenization and encryption
Protegrity is widely implemented for tokenization and encryption of high-risk data elements such as payment and personal identifiers. Tokenization helps reduce the scope of regulated data exposure while preserving referential integrity for downstream systems. The platform supports multiple protection methods (tokenization, encryption, masking) so teams can choose controls based on risk and use case. This aligns well with enterprise requirements where different systems need different protection techniques.
Policy-based protection across environments
The product is designed to apply consistent protection policies across databases, applications, and cloud data platforms. Centralized policy management helps standardize how sensitive fields are protected across multiple teams and data flows. This is useful in organizations with hybrid architectures and multiple data stores. It supports operational use cases where protected data must still be joinable or usable for analytics.
Enterprise integration orientation
Protegrity typically targets complex enterprise deployments that require integration with existing data platforms and security processes. It supports use cases spanning production applications, data lakes/warehouses, and data movement pipelines. This makes it suitable for organizations that need protection embedded into data workflows rather than only generating masked test datasets. It also fits regulated environments that require auditable controls and separation of duties.
Implementation can be complex
Deployments often require architecture planning, integration work, and coordination across security, data engineering, and application teams. Organizations may need professional services or experienced administrators to implement tokenization and policy enforcement correctly. This can increase time-to-value compared with tools focused on narrower, developer-first workflows. Complexity tends to rise in hybrid and multi-cloud environments.
Not primarily synthetic data focused
While Protegrity supports masking and de-identification, its core orientation is protecting real production data in place and in motion. Teams whose primary need is generating high-fidelity synthetic datasets for development and testing may find the workflow less specialized than products built mainly for synthetic data generation. Additional tooling or processes may be required to meet advanced test data management needs. Fit depends on whether the goal is production protection versus test data creation.
Cost and licensing considerations
Enterprise-grade data protection platforms commonly involve licensing that scales with data sources, environments, or usage, which can be a constraint for smaller teams. Ongoing operational overhead (key management, policy administration, monitoring) can add to total cost of ownership. Budgeting may be less predictable when expanding protection coverage across many systems. Organizations should validate pricing drivers during evaluation.
Plan & Pricing
| Plan | Price | Key features & notes |
|---|---|---|
| Developer Edition | Free (no-cost) | Downloadable SDKs / Docker-based local edition for discovery, tokenization, masking, semantic guardrails; intended for dev/test and prototyping. (Official site: Developer Edition pages) |
| Team Edition | Contact sales / Custom pricing (not publicly listed) | Self-contained deployment for teams; local policy control, protectors for common data tools; “Book a demo” indicates sales engagement required. |
| Enterprise Edition | Contact sales / Custom pricing (not publicly listed) | Centralized policy management, scalable cross-cloud enforcement, FIPS/HSM options, formal SLA and procurement support; enterprise pricing not published. |
Seller details
Protegrity Corporation
Stamford, CT, USA
1996
Private
https://www.protegrity.com/
https://x.com/protegrity
https://www.linkedin.com/company/protegrity/
