From SQL Server on premise plus only Fabric Power BI to Fabric

[pmscorca]

Hi,

in order to propose to a my customer, that has SQL Server on premise and him is passing only Fabric Power BI, the entire adoption of Fabric, which could be the points to leverage, beyond saying that Fabric represents an unique/centralized SaaS solution for the complete data flow, from the sources to the presentation/consuming layer for the end users?

My customer has recently invested on SQL Server.

Any suggests to me, please? Many thanks

[v-vpabbu]

Hi @pmscorca,

As we haven’t heard back from you, we wanted to kindly follow up to check if the solution provided for the issue worked? or Let us know if you need any further assistance?
If our response addressed, please mark it as Accept as solution and click Yes if you found it helpful.

Regards,
Vinay Pabbu

[pmscorca]

Hi, many thanks for your reply.

It's curious that you don't talk about mirroring from SQL Server while talk about integration by Fabric Data Factory, perhaps because this feature is in preview yet.

Thanks

[burakkaragoz]

@pmscorca ,

Thank you for your follow-up and for highlighting the topic of SQL Server mirroring to Fabric.

You are absolutely right—SQL Server Mirroring to Microsoft Fabric is a significant feature, and it’s great that you brought it up! The main reason I didn’t mention it previously is because, as you noted, this capability is currently in public preview and not yet fully GA (generally available). However, it does represent a huge leap forward in integrating on-premises SQL Server data into the Fabric ecosystem.

About SQL Server Mirroring in Fabric (Preview):

• Mirroring allows you to replicate tables from your on-premises SQL Server directly into Fabric’s lakehouse or data warehouse in near real-time, with minimal setup.
• This reduces the need for manual ETL or complex pipelines—data changes are automatically synchronized.
• It’s especially valuable for hybrid scenarios, incremental migrations, or real-time analytics use-cases.

Key Benefits of Mirroring:

• Near real-time data availability in Fabric for reporting/analytics (Power BI, Data Science, etc.)
• Simplifies hybrid and migration architectures.
• Reduces overhead compared to traditional Data Factory copy activities or Dataflows.

Current Limitations & Considerations:

• Since mirroring is in preview, it may have certain feature gaps, limitations on supported workloads, and is not recommended for production-critical solutions yet.
• Always review the latest Fabric Mirroring documentation for updates, supported scenarios, and best practices.

How to Position This to Your Customer:

• Present mirroring as an exciting innovation that demonstrates Microsoft’s commitment to seamless hybrid data integration.
• For production or broad-scale workloads, continue to emphasize stable, GA features like Data Gateway, Data Factory pipelines, and Dataflows for now, but mention that mirroring is on the roadmap for even more streamlined integration in the near future.

If you’d like, I can provide example architectures or migration paths that include the mirroring option, or summarize how to set it up in a hybrid environment. Let me know if you want more details!

Thanks again for your insightful follow-up!

[pmscorca]

Hi, thanks but your suggested link doesn't function (content not found).

[v-vpabbu]

Hi @pmscorca,

Attached document links 

https://learn.microsoft.com/en-us/fabric/database/sql/mirroring-limitations 

https://learn.microsoft.com/en-us/fabric/database/mirrored-database/overview 

Regards,

Vinay Pabbu

[burakkaragoz]

Hi @pmscorca ,

Here are some key points and value propositions you can highlight when proposing a transition from on-premise SQL Server + only Power BI (Fabric) to a full Microsoft Fabric adoption:

1. Unified Data Platform:

• Fabric offers a single SaaS platform that covers the entire data lifecycle: data ingestion, engineering, warehousing, real-time analytics, data science, and reporting—all in one place.

2. Seamless Integration with SQL Server:

• Fabric can easily connect to on-premises SQL Server via Dataflows Gen2 or Data Factory pipelines, enabling hybrid scenarios. Your investment in SQL Server is protected, and you can migrate at your own pace.

3. Cost Efficiency & Scalability:

• Fabric eliminates the need for multiple point solutions (ETL tools, data lakes, separate warehouses) and reduces infrastructure management overhead.
• Pay-as-you-go and elastic scaling options optimize resource usage and costs.

4. Enhanced Collaboration & Security:

• Centralized governance, security, and lineage across all data assets.
• Deep integration with Microsoft 365, Azure AD, Purview, and compliance features.

5. Modern Analytics & AI:

• Built-in support for advanced analytics, Python/R notebooks, Spark, and AI/ML workloads.
• Real-time data processing (Eventstreams) and Lakehouse architecture for modern analytics use-cases.

6. Future-Proof & Innovation:

• Fabric is constantly evolving with new features and deep integration across Microsoft’s ecosystem, ensuring your customer’s data estate is ready for future requirements.

7. Migration Pathways:

• Start by connecting on-prem SQL Server to Fabric via Data Gateway.
• Incrementally move ETL, data warehousing, and other workloads into Fabric’s Lakehouse/Data Warehouse as business needs evolve.

8. Value for Existing Investments:

• SQL Server remains a first-class citizen—no need to rip and replace.
• Fabric unlocks additional scenarios (data science, real-time analytics, unified governance) on top of existing SQL workloads.

Summary Table:

Current State With Fabric Adoption

SQL Server on-prem + Power BI	Unified SaaS (ingest, store, transform, viz)
Separate tools, silos	Centralized platform, simplified mgmt
Manual integration	Built-in connectors, automation
Limited scalability	Elastic, cloud-scale compute

References:

• Microsoft Fabric Documentation
• Fabric and SQL Server Integration

Let me know if you want concrete migration steps or technical architecture examples!