Licensing
This document provides an overview of the licensing options for XDM. To ensure maximum flexibility and scalability, the licensing model is modular and based on several key factors:
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Environment and Usage: Based on the number of users and the size of the productive environment.
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Supported Data Connectors: Licensed per connector technology.
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License Packages: Functional scope of the software.
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Optional Components: Additional features that can be licensed individually.
The following sections outline the available options. Detailed descriptions of each variant can be found below.
Usage-Based Licensing Factors
The license fee are additionally determined by:
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Number of Users: The total number of users accessing the software.
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Size of the Productive Environment: The volume of data of productive systems are considered.
Licensed Data Connectors
Database Systems
Support for specific database technologies is licensed separately. The following systems are available:
- Generic JDBC Database
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Connect with any database supporting a JDBC driver. This only supports generic data types, no specific SQL dialects or usage of database-specific utilities.
- Google BigQuery
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Access Google BigQuery as a data source via JDBC and bulk data API.
- IBM Db2 for i
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Access IBM Db2 for i (formerly AS/400) databases via JDBC.
- IBM Db2 for z/OS
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Access IBM Db2 for z/OS databases via JDBC and via IBM’s data transfer utilities.
- IBM Db2 LUW
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Access IBM Db2 for Linux, Unix, and Windows databases via JDBC and via IBM’s data transfer utilities.
- IBM IMS
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Access IBM IMS databases via JDBC over IMS connect.
- Microsoft SQL Server / Azure SQL
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Access Microsoft SQL Server and Azure SQL databases via JDBC and via Microsoft’s bulk data utilities.
- Oracle Database
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Access Oracle databases via JDBC and via Oracle’s data transfer utilities.
- PostgreSQL
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Access PostgreSQL databases via JDBC and via PostgreSQL’s data transfer utilities.
- Snowflake
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Access Snowflake as a data source via JDBC and bulk data API.
- UBS Hainer FileBridge
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Access files in various formats (CSV, Mainframe VSAM and sequential files) as database tables via JDBC.
License Packages
The license packages are designed to cater to different needs and use cases, allowing customers to select the package that best fits their requirements. The following packages are available:
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Essential: The base package with core features for basic use cases.
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Standard: Includes all Essential features plus extended functionality for more advanced scenarios.
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Premium: Full feature set including all modules, integrations, and enterprise-level capabilities.
The table below outlines the packages and their components:
Component |
Essential |
Standard |
Premium |
|---|---|---|---|
Table Copy |
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Row Level Processing |
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Masking |
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Structure Compare |
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Ice Box |
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PII Finder |
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Data Shop |
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Configuration as Code |
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Permission Management |
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Hooks |
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Workflows |
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REST API |
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Test Data Finder |
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Test Data Reservation |
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Cloud Support |
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Events |
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Maintenance Mode |
Optional Components
The following components can be licensed separately to extend the software’s functionality:
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Synthetic Data Generation: Enables the creation of realistic, production-independent test data.
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Synthetic Data Generation with AI: Enhances data generation with AI support.
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Cloud Support: Provides installation and deployment support for cloud-based environments.
| In addition to the components listed above, individual features from the Premium or Standard packages can also be licensed separately. Licensing of these components must be individually negotiated with the vendor. Some components have dependencies on others, so individual license consulting is recommended to determine the best configuration for your needs. |
Detailed Component Descriptions
The following sections provide detailed descriptions of the components:
Synthetic Data Generation
Generates realistic, production-independent test data based on a domain model. Reusable generators can be combined to cover complete business scenarios. Output formats include CSV, JSON, and SQL.
Synthetic Data Generation with AI
Extends data generation with AI support to create test data with minimal effort. Uses domain models and optional meta-information to guide the generation of complete entity instances.
Table Copy
Copies full tables based on name patterns. Supports both native (faster, DB-specific) and compatibility (standard SQL) modes. Optional row reduction rules can be applied.
Row Level Processing
Copies subsets of rows based on a start condition. Automatically follows data dependencies—even beyond foreign key constraints or across databases.
Masking
Modifies data during copying using built-in functions and lookup tables. Masking definitions are reusable across environments and tasks.
Structure Compare
Compares database structures and tracks schema changes. Can generate DDL for setting up empty environments in supported databases.
IceBox
Backs up test data sets for repeated use, ensuring identical test conditions even if data is modified by tests.
PII Finder
Detects sensitive data like names and addresses. Applies data masking methods automatically during copy operations. Includes preconfigured rules and supports customization.
Data Shop
A self-service portal for test data provisioning. Developers and testers can order data; XDM handles orchestration and delivery across systems.
Configuration as Code
Defines the XDM setup in version-controlled, human-readable files. Integrates with Git for automated deployment of configuration changes.
Permission Management
Controls access to configuration objects. Permissions can be assigned to users or groups. Supports LDAP and OpenID integration.
Hooks
Custom scripts triggered during copy processes. Used for data preparation or interaction with external systems.
Workflows
Automates complex multi-step processes beyond copying. Runs tasks in sequence and reuses intermediate results to prepare data for testing.
REST API
Provides full process and configuration control via REST. Supports scheduling, triggering, and importing/exporting configurations.
Test Data Finder
Finds test data that matches user-defined criteria, helping to cover edge cases and improve test quality.
Test Data Reservation
Prevents test data from being used in parallel by multiple testers. Ensures data integrity in shared environments.
Cloud Support
This includes the installation on Kubernetes or OpenShift clusters and enables the capability to run each execution in a separate pod, for a better workload and resource management. Supports cloud-native storage APIs (Azure, Google, AWS) for synchronizing data storage.
Events
Executes custom actions in response to system events. These events can be triggered by user actions or system changes, such as data updates or configuration changes, execution starts or completions and other important operations. For example, this is useful for sending notifications or triggering external workflows.