Compare Mage Dynamic Data Masking vs. Apache Atlas

Apache Atlas

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What is Mage Dynamic Data Masking?

The Mage™ Dynamic Data Masking module, a key component of the Mage data security platform, has been meticulously designed with the end user's needs in mind. In partnership with clients, this module effectively meets their distinct challenges and requirements. As a result, it has evolved to support nearly all conceivable scenarios that businesses may face. Unlike many rival products that typically originate from acquisitions or target specific niches, Mage™ Dynamic Data Masking is tailored to deliver thorough safeguarding of sensitive information accessed by application and database users in live environments. This solution also seamlessly integrates into a company's current IT framework, negating the necessity for significant architectural changes, which facilitates a more effortless implementation for organizations. Furthermore, this thoughtful design underscores a dedication to bolstering data security while enhancing user experience and operational effectiveness, positioning it as a reliable choice for enterprises seeking robust data protection. Ultimately, the Mage™ Dynamic Data Masking module stands out for its ability to adapt to the evolving landscape of data security needs.

What is Apache Atlas?

Atlas is a powerful and flexible suite of crucial governance services that enables organizations to meet their compliance requirements effectively within Hadoop, while also integrating smoothly with the larger enterprise data environment. Apache Atlas equips organizations with the tools to oversee open metadata and governance, allowing them to build an extensive catalog of their data assets, classify and manage these resources, and encourage collaboration among data scientists, analysts, and the governance team. It comes with predefined types for a wide range of metadata relevant to both Hadoop and non-Hadoop settings, and it also allows for the creation of custom types to better handle metadata management. These custom types can include basic attributes, complex attributes, and references to objects, and they can inherit features from other types. Entities serve as instances of these types, containing specific details about the metadata objects and their relationships. Moreover, the provision of REST APIs streamlines interaction with types and instances, thereby improving the overall connectivity and functionality within the data framework. This holistic strategy guarantees that organizations can adeptly manage their data governance requirements while remaining responsive to changing demands, ultimately leading to more effective data stewardship. Furthermore, by utilizing Atlas, organizations can enhance their data integrity and compliance efforts, further strengthening their operational resilience.