Redgate Data Masker for Oracle

Mask sensitive Oracle data for testing

Average rating

Deze score is berekend door AI op basis van publiek beschikbare informatie.
3.8 / 5

About this software

Data Masker for Oracle is a Windows-based tool that replaces sensitive Oracle data with realistic, anonymized test data for non-production environments. It uses configurable masking rules to preserve referential integrity and column relationships, supports large tables, and can run via a graphical UI or command line. The product integrates with SQL Data Catalog and is documented and maintained by Redgate.

Purchase

Redgate Data Masker for Oracle

Redgate Data Masker for Oracle
In Stock
Delivery: 1 working day
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€11,694.19
Free and without obligation

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Benefits

  • Data anonymization: Replaces sensitive Oracle data with realistic, anonymized test values
  • Preserve data relationships: Preserves referential integrity and relationships across tables and columns during masking
  • Windows-based client: Installs on a Windows PC and connects to Oracle via SQL*Net
  • Scale and performance: Handles large tables and datasets, including hundreds of millions of rows
  • Automation and integration: Offers a command-line interface and integrates with SQL Data Catalog for automation

Available languages

  • English

Support information

  • Documentation and guides: Comprehensive online manuals, quick-start guides, and release notes are available on Redgate's documentation site
  • Training courses: Self-paced courses and video tutorials are available through Redgate University
  • Community forums: Product forums and community articles provide user discussions and implementation tips
  • Support services: Redgate offers technical support and purchasing assistance via its support channels
  • Release notes updates: Release notes and version history are published on the documentation and product pages

Frequently asked questions

What is Redgate Data Masker for Oracle?
A data-masking solution for Oracle databases that replaces or obfuscates sensitive production data to create safe, realistic datasets for development, testing, and training while preserving data formats and relationships.
Which use cases does it support?
Common use cases include development, testing, training, and analytics, and supporting compliance by reducing exposure of personal and sensitive data in non-production environments.
How are masking rules configured and applied?
Masking rules map database columns and data types to masking techniques and can be applied across related tables to maintain referential integrity and produce consistent anonymized values.
Can masked data be used safely in application testing?
Masked datasets retain realistic formats and relationships so applications and test suites can run without exposing live personal or sensitive information.