Best Data Masking Software for Spark

Atlas is a flexible and extensible set core foundational governance services that enable enterprises to efficiently and effectively meet their compliance requirements within Hadoop. It also allows integration with the entire enterprise data ecosystem. Apache Atlas offers open metadata management and governance capabilities that allow organizations to create a catalog of their data assets, classify, govern and provide collaboration capabilities around these assets for data scientists, analysts, and the data governance group. Pre-defined types to manage various Hadoop and non Hadoop metadata. Ability to create new types to manage metadata. Types can inherit from other types, and can have simple attributes, complex attributes, and object references. Type instances, also known as entities, are able to capture metadata object details and their relationships. REST APIs allow for easier integration with types and instances.

You have the freedom to choose the anonymization method that best suits your needs - including tokenization, encryption, and masking techniques. This will ensure that sensitive data is protected in a delicate balance between security and performance. You can choose from over 60 different anonymization methods to protect sensitive data. Anonymization methods that provide consistent results across datastores and applications will help you maintain referential integrity. Anonymization methods that provide both performance and protection. You can choose to encrypt, tokenize or mask data depending on the use case. There are many ways to anonymize sensitive data. Each method provides adequate security and data usability. Protect sensitive data across data storage and applications, and maintain referential integrity. You can choose from a range of NIST-approved encryption or tokenization algorithms.

iMask protects sensitive data at the Application Layer as well as the Database Layer. It offers flexible solutions that can be used for all types of use and all users, small, medium and large. Mask sensitive data at both the application and database levels to ensure your data's protection in production. You can set up rules in the product UI to allow role-based and user-based access controls that control who can access your sensitive information. You have the option to choose from more than 40 anonymization methods to maintain data consistency between production and nonproduction instances. You can set authorization rules to restrict who can see sensitive data based on geography, roles, departments, and other factors. Secure anonymization protocols can be enabled without affecting performance. Database embedded approach allows data to be deidentified without any changes in the application architecture or security protocols.