Features, pricing, ratings, and pros and cons, compared head to head.
DataStealth is a commercial data masking & synthetic data tool by DataStealth. Randtronics DPM easyData is a commercial data masking & synthetic data tool by Randtronics. Compare features, ratings, integrations, and community reviews side by side to find the best data masking & synthetic data fit for your security stack. Independent and vendor-neutral: we never sell rankings.
Based on our analysis of NIST CSF 2.0 coverage, core features, integrations, company size fit, here is our conclusion:
Mid-market and enterprise teams protecting sensitive data across fragmented infrastructure,on-prem databases, cloud APIs, legacy mainframes, and SaaS together,should evaluate DataStealth for its agentless inline masking that actually works across those disparate environments without forcing rip-and-replace. The platform covers all four NIST asset and data security functions (ID.AM, ID.RA, PR.DS, DE.CM) and deploys via gateway or proxy rather than requiring agents on every system, which matters when you're dealing with air-gapped or mainframe systems that block typical tooling. Skip this if your primary concern is detection and response; DataStealth prioritizes classification and protection over behavioral anomaly hunting.
Mid-market and enterprise teams protecting sensitive data across SQL databases and flat files without custom code will find DPM easyData's agentless connectors and format-preserving encryption straightforward to deploy. FIPS 140-3 L3/4 and Common Criteria EAL 4+/5+ certification with AES-256 and HSM support satisfy regulated compliance requirements; the Database Clientless option eliminates agent overhead across PostgreSQL, MySQL, Oracle, and MariaDB. Skip this if you need application-layer tokenization at scale or cross-platform file masking beyond structured databases; DPM easyData's strength is field-level database protection, not ecosystem coverage.
Inline data protection platform for on-prem, legacy, hybrid & cloud envs.
Field-level data protection via encryption, masking & tokenization for DBs and files.
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Common questions about comparing DataStealth vs Randtronics DPM easyData for your data masking & synthetic data needs.
DataStealth: Inline data protection platform for on-prem, legacy, hybrid & cloud envs. built by DataStealth. Core capabilities include Real-time agentless data discovery and classification across databases, files, APIs, SaaS, and event streams, Inline data masking, tokenization, and encryption applied as data flows, Coverage for on-premises, cloud, hybrid, legacy, mainframe, and air-gapped systems..
Randtronics DPM easyData: Field-level data protection via encryption, masking & tokenization for DBs and files. built by Randtronics. Core capabilities include Field-level encryption, format-preserved encryption, masking, tokenization, anonymization, and pseudonymization, No-code database FLP via Database Connector (MS SQL, Oracle), No-code agentless database FLP via Database Clientless (MS SQL, MariaDB, PostgreSQL, MySQL, Oracle)..
Both serve the Data Masking & Synthetic Data market but differ in approach, feature depth, and target audience.
DataStealth differentiates with Real-time agentless data discovery and classification across databases, files, APIs, SaaS, and event streams, Inline data masking, tokenization, and encryption applied as data flows, Coverage for on-premises, cloud, hybrid, legacy, mainframe, and air-gapped systems. Randtronics DPM easyData differentiates with Field-level encryption, format-preserved encryption, masking, tokenization, anonymization, and pseudonymization, No-code database FLP via Database Connector (MS SQL, Oracle), No-code agentless database FLP via Database Clientless (MS SQL, MariaDB, PostgreSQL, MySQL, Oracle).
DataStealth is developed by DataStealth. Randtronics DPM easyData is developed by Randtronics. Vendor maturity, funding stage, and team size can be important factors when evaluating long-term viability and support quality.
DataStealth and Randtronics DPM easyData serve similar Data Masking & Synthetic Data use cases: both are Data Masking & Synthetic Data tools, both cover Encryption, Tokenization. Review the feature comparison above to determine which fits your requirements.
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