Here are a few options:
1. Azure Data Sync This is a built-in feature for Azure SQL Database that allows bi-directional or one-directional synchronization between databases.
Key Features:
- Filter Support: You can apply filters on the rows to synchronize only specific data (e.g., rows from the last 3 months).
- Automatic Sync: Sync can be scheduled at regular intervals.
- Conflict Resolution: Offers conflict resolution policies (e.g., last writer wins).
Steps:
- Set up Azure Data Sync in the Azure portal.
- Define a Sync Group where one database acts as the hub and the other as a member.
- Add the tables you wish to synchronize and configure filters to limit rows (e.g.,
WHERE DateColumn >= DATEADD(MONTH, -3, GETDATE())
).
Pros:
- Fully managed service with minimal maintenance.
- Easy to set up and monitor in the Azure portal.
Cons:
- Only supports Azure SQL Database or on-premises SQL Server.
- Less flexibility for custom transformations or complex business rules.
2. Azure Data Factory (ADF) This offers more flexibility and supports complex ETL and synchronization scenarios.
Key Features:
- Filter Support: You can use dynamic queries to extract only the required rows (e.g., data from the last 3 months).
- Custom Logic: Use mapping data flows or transformations for additional processing.
- Integration: Supports diverse data sources and destinations, making it suitable for hybrid systems.
Steps:
- Create a pipeline in Azure Data Factory.
- Use the Copy Data activity with a query to filter the data to synchronize.
- Configure the destination database and run the pipeline on a schedule.
Pros:
- Very flexible and supports complex transformations.
- Scales well for large datasets and complex scenarios.
Cons:
- More complex to set up compared to Azure Data Sync.
- May require additional compute resources for transformation activities.
3. Change Data Capture (CDC) This is a feature that tracks changes (inserts, updates, deletes) in source tables and makes them available for synchronization.
Key Features:
- Incremental Updates: Only captures and syncs changes since the last synchronization.
- Filters: You can apply custom logic during synchronization to filter rows (e.g., based on timestamps).
- Custom Control: Gives you more flexibility to handle synchronization at the application level.
Steps:
- Enable CDC on the source database.
- Use tools like Azure Data Factory or custom ETL scripts to extract changes from CDC tables.
- Apply filters (e.g., date filters) and synchronize to the destination database.
Pros:
- Efficient for synchronizing large databases with frequent changes.
- Provides fine-grained control over synchronization.
Cons:
- Requires additional configuration and maintenance.
- Application logic may be required to handle synchronization conflicts.
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hth
Marcin