Efficiently Transferring a 30-Million-Row Table Between Fabric Tenants in Different Organizations

@Likitha Bommasani

To efficiently copy a 30 million-row table from Fabric Tenant A to Fabric Tenant B (especially when these tenants belong to different organizations), here are some best practices and strategies:

Utilize Azure Data Factory (ADF) or Synapse Pipelines

Leverage ADF to create scalable and secure data pipelines.

Use Copy Activity for straightforward data copying and Data Flows for any necessary transformations.

Break Data into Manageable Chunks

Instead of transferring all rows at once, split the data into smaller chunks based on logical partitions (e.g., date ranges or row IDs).

This approach helps reduce load and enhances performance.

Adopt Efficient Data Formats

Use compressed formats like Parquet or ORC to minimize transfer time and storage costs.

These formats are optimized for performance and can significantly reduce the size of the data being transferred.

Implement Secure Authentication

Utilize Managed Identity or Service Principal for secure authentication between tenants.

This method eliminates the need for manual credential management and enhances security.

Consider Delta Loads or Change Data Capture (CDC)

For frequently updated data, use CDC or delta load strategies to transfer only the changes since the last load.

This reduces the volume of data movement and optimizes transfer efficiency.

Ensure Network Security with Data Gateway

If there are network restrictions, employ an Azure Data Gateway to facilitate secure data transfer without exposing sensitive information.

Optimize Performance

Use the Azure Integration Runtime for high-performance data transfers.

Ensure both tenants are located in nearby Azure regions to minimize latency.

Monitor and Implement Retry Logic

Set up monitoring to track the progress and identify any failures during the transfer.

Implement retry logic to handle transient errors automatically.

Conduct Post-transfer Validation

After the transfer, validate the data integrity by comparing row counts or performing data checks.

This step ensures that all data has been accurately transferred.

By following these strategies, you can ensure that the transfer process is efficient, secure, and reliable.

I hope this information helps. Please do let us know if you have any further queries.

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