DvSchemaSync is a powerful Windows application designed to bridge the gap between Microsoft Dataverse and Azure SQL Database. Whether you need to synchronize production data for reporting and analytics, or generate realistic test data for development environments, DvSchemaSync provides an intuitive, efficient solution.
What is DvSchemaSync?
DvSchemaSync (also known as Data Mission Tools) is developed by Mission Impact Partners to serve two primary functions:
Schema and Data Synchronization: Automatically replicate your Dataverse tables, columns, and data to Azure SQL Database. This enables you to run complex reports, build dashboards, and perform analytics without impacting your Dataverse environment's performance.
Dummy Data Generation: Create realistic, localized test data directly in your Dataverse development or sandbox environments. Generate accounts, contacts, and related records with country-specific formatting for the US, UK, France, Germany, and Canada.
Key Benefits
Unlock Your Data for Reporting: Move your Dataverse data to Azure SQL where you can use familiar SQL tools, Power BI, and other analytics platforms without API limitations.
Preserve Schema Integrity: DvSchemaSync automatically creates matching table structures in Azure SQL, handling data type conversions and option set mappings.
Secure Credential Management: All connection credentials are stored securely using Windows Credential Manager, not in plain text files. Supports Microsoft Entra App Registration for Dataverse and both Entra and SQL authentication for Azure SQL.
High Performance: Parallel processing and connection pooling enable synchronization rates of 50+ records per second, even with large datasets.
Multi-Language Support: The application interface is available in English, German, French and Spanish.
Who Is DvSchemaSync For?
System Administrators who need to replicate Dataverse data for backup or reporting purposes
Business Analysts who want to query CRM data using SQL rather than complex FetchXML
Developers who need realistic test data in sandbox environments
Data Engineers building data pipelines that require Dataverse data in a relational format