[Home](https://cybersectools.com/) / [Categories](https://cybersectools.com/categories) / [Data Protection](https://cybersectools.com/categories/data-protection) / Data Masking & Synthetic Data # Data Masking & Synthetic Data Solutions 2026 Data masking and synthetic data solutions solve a problem every security team eventually hits: developers, analysts, and test environments need realistic data, but they should never touch the real thing. These solutions either transform production data so it keeps its shape and statistical behavior while stripping out anything sensitive, or they generate entirely new datasets that mimic the original without being derived from real records. The category spans static masking for non-production copies, dynamic masking that redacts on the fly based on who is asking, tokenization and format-preserving encryption, and generative approaches that produce synthetic data for testing, analytics, and AI model training. For a CISO, this is how you shrink the blast radius of your lower environments and satisfy GDPR, HIPAA, PCI DSS, and data residency rules without grinding engineering velocity to a halt. 25 commercial products · [What is Data Masking & Synthetic Data?](https://cybersectools.com/glossary/data-masking) ## Featured on CybersecTools Paid placement: Featured vendors pay for a plan and show first. The shortlist positions are earned. [How we label paid slots](https://cybersectools.com/methodology) - [Strike48 Platform](https://www.strike48.com/platform?utm_source=cybersectools.com&utm_medium=featured) (Featured): Security Operations - [SecureIntent](https://secureintent.ai/?utm_source=cybersectools.com&utm_medium=featured) (Featured): Data Protection - [Fortra](https://www.fortra.com/?utm_source=cybersectools.com&utm_medium=featured) (Featured): Data Protection - [Lunar](https://lunarcyber.com/?utm_source=cybersectools.com&utm_medium=featured) (Featured): Threat Intelligence - [Hudson Rock](https://www.hudsonrock.com/?utm_source=cybersectools.com&utm_medium=featured) (Featured): Threat Intelligence - [Daylight Security](https://daylight.ai/?utm_source=cybersectools.com&utm_medium=featured) (Featured): Security Operations ## Compare in Data Masking & Synthetic Data The most-opened side-by-side pages for Data Masking & Synthetic Data solutions. - [Anonomatic PII Vault vs Protecto High-Volume Data Masking](https://cybersectools.com/compare/anonomatic-pii-vault-vs-protecto-high-volume-data-masking) - [Anonomatic PII Vault vs Limina Data De-identification](https://cybersectools.com/compare/anonomatic-pii-vault-vs-private-ai-text) - [Protegrity Vaultless Tokenization vs Skyflow Fintech Data Privacy Vault](https://cybersectools.com/compare/protegrity-vaultless-tokenization-vs-skyflow-fintech-data-privacy-vault) - [Protegrity Data Protection vs Thales CipherTrust Application Data Protection](https://cybersectools.com/compare/protegrity-data-protection-vs-thales-ciphertrust-application-data-protection) - [DataStealth Cloud Deployment vs eXate Datagator & Gatorset](https://cybersectools.com/compare/datastealth-cloud-deployment-vs-exate-datagator-and-gatorset) - [Anonos Data Embassy vs eXate Datagator & Gatorset](https://cybersectools.com/compare/exate-datagator-and-gatorset-vs-anonos-data-embassy) ## The Data Protection market Company data as of 2026-11-03 - 252 companies sell in this market - $1.8B raised in 28 rounds in the last 12 months - 9 acquired in the last 12 months - 12 founded in the last two years [Explore the Data Protection market on Mandos](https://mandos.io/data/companies?utm_source=cybersectools.com&utm_medium=category&utm_campaign=data-protection) ## Data Masking & Synthetic Data solutions All 30 · Free 5 · Commercial 25 1. [Pimloc Secure Redact](https://cybersectools.com/tools/pimloc-secure-redact) (Data Masking & Synthetic Data): AI platform for automated video redaction and privacy compliance. 2. [Skyflow for GenAI](https://cybersectools.com/tools/skyflow-for-genai) (Data Masking & Synthetic Data): Data privacy vault to protect PII across the full LLM/GenAI lifecycle. 3. [Skyflow Fintech Data Privacy Vault](https://cybersectools.com/tools/skyflow-fintech-data-privacy-vault) (Data Masking & Synthetic Data): PCI-compliant data privacy vault enabling multi-payment processor support. 4. [Skyflow Healthcare Data Privacy Vault](https://cybersectools.com/tools/skyflow-healthcare-data-privacy-vault) (Data Masking & Synthetic Data): HIPAA-compliant PHI data privacy vault with zero trust architecture. 5. [Randtronics DPM easyData](https://cybersectools.com/tools/randtronics-dpm-easydata) (Data Masking & Synthetic Data): Field-level data protection via encryption, masking & tokenization for DBs and files. 6. [Protecto High-Volume Data Masking](https://cybersectools.com/tools/protecto-high-volume-data-masking) (Data Masking & Synthetic Data): Scalable PII data masking for high-volume enterprise workloads. 7. [Limina Data De-identification](https://cybersectools.com/tools/private-ai-text) (Data Masking & Synthetic Data): On-prem PII detection, redaction & replacement tool for unstructured text. 8. [Odaseva Data Masking for Salesforce](https://cybersectools.com/tools/odaseva-data-masking-for-salesforce) (Data Masking & Synthetic Data): Salesforce-native data masking tool for sandbox & prod anonymization. 9. [Mage Data - Asset Class Aware Data Protection](https://cybersectools.com/tools/mage-data-asset-class-aware-data-protection) (Data Masking & Synthetic Data): Links asset classification to data protection policies for consistent data security. 10. [eXate Datagator & Gatorset](https://cybersectools.com/tools/exate-datagator-and-gatorset) (Data Masking & Synthetic Data): ETL & JDBC-based data-at-rest protection with access control & policy mgmt. 11. [DataStealth On-Premise](https://cybersectools.com/tools/datastealth-on-premise) (Data Masking & Synthetic Data): On-prem data tokenization, masking & encryption for air-gapped environments. 12. [DataStealth Hybrid](https://cybersectools.com/tools/datastealth-hybrid) (Data Masking & Synthetic Data): Unified data protection platform for hybrid on-prem and cloud environments. 13. [DataStealth Cloud Deployment](https://cybersectools.com/tools/datastealth-cloud-deployment) (Data Masking & Synthetic Data): Cloud-native data tokenization, masking & encryption for AWS, Azure, and GCP. 14. [DataStealth Data Protection](https://cybersectools.com/tools/datastealth-data-protection) (Data Masking & Synthetic Data): Data security platform offering tokenization, masking & encryption per data element. 15. [DataStealth](https://cybersectools.com/tools/datastealth) (Data Masking & Synthetic Data): Inline data protection platform for on-prem, legacy, hybrid & cloud envs. 16. [brighter Redact Edge](https://cybersectools.com/tools/brighter-redact-edge) (Data Masking & Synthetic Data): On-device, real-time anonymization of faces and license plates at the edge. 17. [Anonos Data Embassy](https://cybersectools.com/tools/anonos-data-embassy) (Data Masking & Synthetic Data): Data protection platform enforcing policies for secure cross-border data use. 18. [Nymiz Data Anonymization Software](https://cybersectools.com/tools/nymiz-data-anonymization-software) (Data Masking & Synthetic Data): AI-driven data anonymization & redaction software for documents & databases 19. [Anonomatic PII Vault](https://cybersectools.com/tools/anonomatic-pii-vault) (Data Masking & Synthetic Data): PII de-identification vault with patented PolyAnonymization technology 20. [Privacera Enterprise Data Encryption and Masking Solutions](https://cybersectools.com/tools/privacera-enterprise-data-encryption-and-masking-solutions) (Data Masking & Synthetic Data): Enterprise data masking and encryption solution for sensitive data protection 21. [Glasswall Find and Redact](https://cybersectools.com/tools/glasswall-find-and-redact) (Data Masking & Synthetic Data): Automated file redaction tool for sensitive data in documents and metadata. 22. [Thales CipherTrust Application Data Protection](https://cybersectools.com/tools/thales-ciphertrust-application-data-protection) (Data Masking & Synthetic Data): SDK for app-level data encryption, tokenization & masking with centralized mgmt 23. [Protegrity Vaultless Tokenization](https://cybersectools.com/tools/protegrity-vaultless-tokenization) (Data Masking & Synthetic Data): Data protection platform offering vaultless tokenization and multiple methods 24. [Protegrity Data Protection](https://cybersectools.com/tools/protegrity-data-protection) (Data Masking & Synthetic Data): Field-level data protection platform with tokenization, encryption & masking. Page 1 of 2. Next: https://cybersectools.com/categories/data-masking.md?page=2 25 commercial products · 5 free products under [Free solutions](https://cybersectools.com/free) | Related: [Key Management](https://cybersectools.com/categories/key-management) · [Backup as a Service](https://cybersectools.com/categories/backup-as-a-service) · [Data Classification](https://cybersectools.com/categories/data-classification) · [Data Loss Prevention](https://cybersectools.com/categories/dlp) · [Data Security Posture Management](https://cybersectools.com/categories/dspm) ## How to choose Data Masking & Synthetic Data solutions - Confirm it preserves referential integrity and data relationships across tables and systems, not just single columns, or masked data breaks downstream tests. - Check which masking modes it supports: static for non-production copies, dynamic for role-based redaction at query time, and format-preserving so data still validates. - Evaluate the synthetic data engine if you need it: how faithfully it reproduces distributions and edge cases, and what re-identification risk it leaves behind. - Examine sensitive-data discovery and classification, since the solution can only protect fields it can reliably find and tag across your sources. - Verify connector coverage for your actual stack: relational databases, data warehouses, lakes, and the SaaS sources where regulated data lives. - Benchmark performance at production scale and how cleanly it slots into CI/CD so masking does not become the bottleneck for environment refreshes. ## Data Masking & Synthetic Data Solutions FAQ Common questions about Data Masking & Synthetic Data solutions: how to choose, pricing and comparisons. ### What is data masking and synthetic data generation? Data masking transforms sensitive values in a dataset so they stay usable but no longer expose real information, for example swapping real customer names and card numbers for realistic fakes. Synthetic data goes further by generating brand-new records that statistically resemble the source without being copied from it. Both let teams use realistic data in testing, analytics, and AI training while removing the underlying privacy and compliance risk. ### How is data masking different from encryption or tokenization? Encryption is reversible by design: with the key, you recover the original data, so the sensitive value still exists in the system. Tokenization swaps values for tokens mapped in a separate vault. Masking and synthetic data are usually meant to be irreversible, producing a permanently de-identified dataset with no path back to the original. You often want both: encryption to protect production, masking or synthetic data to protect everything downstream of it. ### How should I evaluate a data masking or synthetic data solution? Check whether it preserves referential integrity across tables and systems, since broken relationships make masked data useless for testing. Examine the breadth of connectors for your databases, warehouses, and SaaS sources, the masking techniques offered (static, dynamic, format-preserving, synthetic), how it discovers and classifies sensitive fields, and how it handles re-identification risk. Performance at production scale and integration into CI/CD pipelines also separate the serious solutions from the demos. ### Do I need synthetic data, or is masking enough? Masking is enough when you need production-accurate data for functional testing and your main goal is de-identification. Synthetic data earns its place when you cannot copy production at all due to regulation or residency, when you need volumes or edge cases that do not exist in production, or when training AI models where any link back to real records is unacceptable. Many teams run both, choosing per use case rather than standardizing on one. ### Are free or open-source masking solutions good enough, or should I buy commercial? Open-source masking libraries handle straightforward field-level obfuscation and suit small, single-database scenarios. Commercial platforms tend to win on automated sensitive-data discovery, referential integrity across many systems, dynamic masking with policy-based access, audit trails for compliance, and synthetic data generation. If masking touches regulated data across multiple sources or must be defensible to auditors, the commercial solutions usually pays for itself. --- Source: https://cybersectools.com/categories/data-masking For AI agents: every CybersecTools shortlist is listed at https://cybersectools.com/shortlists.md. More on the Data Masking & Synthetic Data vendors: funding, momentum, hiring and news, plus the full product and company record, are available through the Mandos MCP Server (paid plans), which connects to AI assistants: https://mandos.io/mcp?utm_source=cybersectools.com&utm_medium=category-md