Data Protection and Cryptography vs DataStealth On-Premise: Side-by-Side Comparison (2026)

Data Protection and Cryptography

Developers and security teams building applications that need lightweight data masking without infrastructure overhead should reach for Data Protection and Cryptography. The free pricing and 630 GitHub stars signal active use in production environments where byte-level manipulation of sensitive data needs to happen inside application code rather than in a separate gateway. Skip this if your requirement is policy-driven data discovery across your entire data estate; this tool assumes you already know what to mask and where.

DataStealth On-Premise

Mid-market and enterprise teams protecting sensitive data in air-gapped or heavily regulated environments should pick DataStealth On-Premise for its ability to enforce field-level masking and tokenization without sending data outside your infrastructure. The inline gateway and sidecar deployment models work across SQL, NoSQL, Kafka, and Kubernetes, so you're not rebuilding policy for every data store; BYOK and on-prem HSM integration mean keys never leave your network. Skip this if your data lives primarily in SaaS platforms or you need a lightweight, API-first masking layer; DataStealth is built for teams managing their own infrastructure and willing to maintain a stateful proxy tier.