DvSchemaSync's primary function is synchronizing data from Microsoft Dataverse to Azure SQL Database. This enables you to leverage your Dataverse data for reporting, analytics, and integration scenarios without impacting your production environment.
What Schema Sync Does
The synchronization process performs three key operations:
Schema Replication: Automatically creates matching table structures in Azure SQL based on your Dataverse table definitions. Data types are mapped appropriately, and option sets are converted to readable values.
Data Transfer: Copies records from Dataverse to Azure SQL using high-performance parallel processing. Large tables are handled efficiently with batching and pagination.
Always inserts: The process drops existing tables and recreates net news with every sync, the tool is meant to provide a quick way for administrators to dump data from Dataverse. If you require incremental syncing, please see our Data Mission Sync tool (https://datamission.io) .
Typical Use Cases
Data Validation: You may want to validate data en masse using SQL scripts rather then API calls, useful when validating post migration steps to new Dataverse environments or checking on the results of third-party integrations to your Dataverse environment.
Power BI Reporting: Connect Power BI directly to Azure SQL for faster queries and no Dataverse API throttling concerns.
Data Warehousing: Feed Dataverse data into your enterprise data warehouse for cross-system analytics.
Custom Applications: Build applications that read from Azure SQL instead of making direct Dataverse API calls.
Backup and Archive: Maintain a secondary copy of your Dataverse data in a standard SQL database format.
Complex Queries: Run SQL queries that would be difficult or impossible through the Dataverse API, including complex joins and aggregations.
How It Works
DvSchemaSync uses a step-by-step wizard to guide you through the synchronization process:
- Start Sync — From the landing page, click "Start Sync →" to launch the sync wizard.
- Step 1: Dataverse Connection — Select or configure your Dataverse connection and test it.
- Step 2: SQL Server Connection — Select or configure your Azure SQL connection and test it.
- Step 3: Sync Options — Select the entities to synchronize and configure synchronization options.
- Sync Progress — Monitor the synchronization progress in real-time until completion.
Performance
DvSchemaSync is optimized for performance:
• Parallel processing enables 50+ records per second throughput
• Connection pooling minimizes database connection overhead
• Configurable batch sizes let you balance speed with resource usage
• Built-in rate limiting respects Dataverse API limits