Protegrity & IBM

Features & Capabilities

Protect sensitive data across IBM core systems and modern data workflows while maintaining centralized policy and keeping protected information useful for approved operational, analytics, and data-processing needs.

• 01

  Granular Data Protection Across IBM Platforms: Fine-grained control at the field and column level 

  Why It Matters

  Sensitive information such as PII, PHI, and financial data can exist across mainframe applications, Db2 databases, files, and downstream data pipelines. Applying protection at the field or column level helps reduce unnecessary exposure while allowing applications and approved workflows to continue using the data they need.

  How It Works

  Protegrity applies protection methods such as tokenization, encryption, and masking to selected sensitive data across IBM environments including Db2 on z/OS, COBOL applications, VSAM, IMS, Db2 LUW, DataStage, and StreamSets. Centrally managed policy determines how protected data is handled across supported workloads.

• 02

  Seamless Integration with IBM Mainframe and Databases: Security without disruption 

  Why It Matters

  Mission-critical IBM systems often contain some of an organization’s most sensitive and long-lived data. Protection needs to operate within those environments without requiring organizations to redesign the applications and data-processing patterns that depend on them.

  How It Works

  Protegrity supports IBM mainframe protection through integration patterns including Db2 FIELDPROC, EDITPROC, and UDFs, along with application and file protection for COBOL, PL/I, VSAM, and IMS environments. Db2 LUW workloads can also apply database-level protection through supported protectors and UDF-based patterns.

• 03

  ETL and Streaming Protection with DataStage & StreamSets: Secure pipelines end-to-end 

  Why It Matters

  Protegrity embeds tokenization and encryption directly into IBM DataStage jobs and StreamSets pipelines, ensuring that sensitive data remains protected as it moves across hybrid and multi-cloud data landscapes. This end-to-end protection is critical for organizations managing complex ETL and streaming workflows, as it prevents data exposure during transformation and transit.

  How It Works

  For instance, a healthcare organization uses DataStage integrated with Protegrity APIs to tokenize PHI during ETL jobs, while StreamSets applies policy-driven masking in real time for streaming workloads. This ensures that sensitive health information is consistently protected, supporting HIPAA compliance and secure data sharing across diverse platforms.

• 04

  AI & Analytics Enablement: Unlock insights from protected legacy and modern data

  Why It Matters

  Protegrity-protected data across IBM systems remains fully usable for business intelligence, reporting, and AI/ML workloads, regardless of whether the data originates from mainframe, DB2, or ETL pipelines. This enables organizations to drive innovation and gain actionable insights from governed datasets without exposing sensitive raw values, supporting secure digital transformation initiatives. 

  How It Works

  Retailers, for example, can combine tokenized sales and customer data from mainframe and DB2 systems into analytics platforms, enabling advanced personalization initiatives while maintaining PCI compliance. This approach allows for secure, scalable analytics that respects privacy and regulatory requirements.

• 05

  Compliance Simplification: Consistent enforcement across IBM ecosystems 

  Why It Matters

  Centralized policies in Protegrity’s Enterprise Security Administrator (ESA) ensure consistent enforcement of GDPR, HIPAA, PCI-DSS, and other regulatory frameworks across mainframe, DB2, DataStage, and StreamSets. This unified policy management simplifies compliance, reduces the risk of audit findings, and streamlines governance across complex hybrid environments.

  How It Works

  Enterprises can reduce audit preparation time by 40% through automated reporting of Protegrity’s protection policies enforced across their IBM environments. This automation not only improves compliance readiness but also provides clear, auditable evidence of data protection for regulators and stakeholders.