Forum Discussion
Advocate IAzure Synapse Link for Dataverse in a Fabric architecture
Hi Luigia-Costabil ,
Thanks for reaching out to Microsoft Fabric Community and Thanks to Vinodh247 for providing meaningful insights.Converting the Append Only CSV exports into Delta tables using Fabric notebooks does not inherently reduce the benefits of Synapse Link change tracking. The main consideration is data freshness, as the Delta Bronze layer will only reflect changes after the Fabric notebook or pipeline has processed the latest exported files.
Regarding Append Only mode, Microsoft documentation states that create, update, and delete changes are written as additional records in the destination files, and delete operations can be identified through the IsDelete column. This supports incremental processing scenarios.
However, the documentation does not explicitly state that the exported files should be treated as a complete audit trail containing every intermediate change event. Therefore, while Append Only preserves the changes exported by Synapse Link, any requirements for full historical auditing should be validated against your specific business needs.
A common Fabric approach is to retain the exported CSV files as the raw layer and load them into Delta Bronze tables using Fabric Spark notebooks or pipelines, allowing downstream workloads to benefit from Delta Lake capabilities while preserving the original exports.
For Reference:
Advanced configuration options in Azure Synapse Link Link your Dataverse environment to Microsoft Fabric and unlock deep insights
Export Dataverse data in Delta Lake formatBest Regards,
Abdul Rafi
Community SupportHi Luigia-Costabil ,
Thankyou for reaching out to Microsoft Fabric Community.
Yes, Azure Synapse Link's CSV export can be used as a raw landing or Bronze layer in a Medallion Architecture. This approach preserves the source data in its original form and can be suitable for organizations that want to minimize transformations during ingestion. However, many Fabric implementations subsequently convert the data to Delta format, as Fabric Lakehouse workloads are optimized for Delta tables.
When data remains in CSV format, there are a few considerations. Query performance is generally lower compared to Delta tables, storage usage tends to be higher, and schema changes often require additional handling. While Synapse Link provides change tracking metadata that can support incremental processing, implementing CDC or SCD Type 2 patterns typically requires more custom logic than a Delta-based approach. Data consumption can also become more complex since schema management and data consistency must be handled outside the file format itself.
Regarding costs, ADLS Gen2 charges are primarily based on storage consumption and transaction volume. Compute costs depend on the processing engine used, data volume, and refresh frequency. Incremental processing is commonly used to help optimize compute consumption.
Using Fabric Spark instead of a Synapse Spark Pool to create the Bronze Delta layer is a valid architecture pattern and aligns well with a Fabric-first strategy.
This allows the raw exported files to be retained while enabling downstream layers to benefit from Delta Lake features such as improved performance, schema evolution, and efficient merge operations.
For Reference :
Create an Azure Synapse Link for Dataverse with Azure Data Lake
Export Dataverse data in Delta Lake format
Azure Synapse FAQ's
Best Regards,
Abdul Rafi