BMC AMI DevX vs Mage Static Data Masking comparison

BMC AMI DevX is a mainframe DevOps platform for IBM Z environments that helps development and platform engineering teams increase release velocity, reduce change risk, and build a sustainable mainframe developer workforce.

Whether the priority is attracting the next generation of mainframe talent, safely evolving decades of business-critical code, accelerating release velocity, or demonstrating development ROI to leadership — BMC AMI DevX is designed to address all on a single platform. Teams can connect existing tools and adopt capabilities incrementally using an open-borders integration approach.

A 2025 Forrester Total Economic Impact study found that customers using BMC AMI DevX onboarded developers 50% faster, completed code changes 33% faster, increased release frequency by 50%, and reduced change failure rate by 33%.

Key capabilities:

• Modern IDE integration (VS Code, Eclipse) with a unified development environment that reduces context switching
• AI-powered code analysis including dependency mapping, impact analysis, and runtime execution path visualization
• Automated unit, functional, integration, and performance testing with code coverage analysis
• Git-compatible CI/CD integration with event-driven webhooks and an open plug-in library
• DORA metrics and DevOps KPI tracking with AI/ML anomaly detection across the mainframe SDLC

Mage Static Data Masking provides a comprehensive approach to privacy protection by anonymizing sensitive data at scale, ensuring compliance with global data regulations.

Mage Static Data Masking focuses on transforming sensitive data into anonymized form, facilitating safe usage across development, testing, and analytics environments. It plays a crucial role in securing personal information by replacing specific data within a dataset while preserving its overall structure and value for intelligence purposes. The implementation of this technology aids in ensuring regulatory compliance and minimizing data breach risks effectively. Whether applied within financial services, healthcare, or governmental sectors, this tool bolsters data security and operational efficiency.

• Data Anonymization: Provides comprehensive anonymization processes that maintain data usability while addressing privacy concerns.
• Scalability: Supports large-scale data environments, making it suitable for extensive datasets.
• Integration Capabilities: Easily integrates with existing infrastructure, facilitating seamless adoption.

• Compliance Assurance: Aids compliance with international data protection regulations.
• Risk Reduction: Minimizes the potential for data breaches with robust masking techniques.
• Cost Efficiency: Reduces costs associated with data protection by streamlining processes.

In industries like healthcare and finance, Mage Static Data Masking is implemented to safeguard personal and financial information while enabling innovation through analytics and development testing. Its robust framework supports the secure handling of data without inhibiting operations, making it an essential tool across sectors requiring rigorous data protection measures.