Welcome to our Microsoft Fabric Tutorial Series! Data Mirroring in Fabric is a powerful feature that transforms how businesses replicate and analyse their cloud data. This step-by-step guide will help you understand, set up, and optimize data mirroring within Microsoft Fabric to unlock near real-time insights faster and easier than ever.
What is Data Mirroring in Fabric?
Data Mirroring in Fabric enables continuous replication of data from operational sources into Microsoft Fabric’s OneLake. Unlike traditional ETL processes, it ensures your data is always fresh, stored in open Delta Lake format, and ready for analytics, BI, and AI workloads.
Benefits of Using Data Mirroring in Fabric
- Near real-time data replication reduces latency between data updates and analytics.
- Simplifies data integration by eliminating complex ETL pipelines.
- Unifies data estates by breaking down silos and centralizing analytics.
- Improves compliance and governance by using Fabric’s built-in access controls.
Types of Data Mirroring in Fabric
| Type | Description | Ideal Use Case |
|---|---|---|
| Database Mirroring | Replicates complete databases or selected tables into OneLake for analytics. | Comprehensive reporting, BI, and unified data solutions. |
| Metadata Mirroring | Mirrors only metadata like tables and schema — data stays on source systems. | Lightweight metadata management and cataloging. |
| Open Mirroring | External apps can push change files directly to Fabric’s mirrored delta tables. | Custom integrations and programmable data ingestion. |
How Does Data Mirroring Work?
- Initial Data Snapshot: Fabric captures a baseline copy of the source data.
- Change Data Capture (CDC): Incremental changes (inserts/updates/deletes) are detected in real time.
- Delta Lake Storage: Data is stored in the open Delta Lake parquet format in OneLake.
- Query Access: Analysts can run SQL queries or use Power BI on mirrored data without impacting sources.
- Monitoring: Fabric provides dashboards to track replication health and troubleshoot errors.
Supported Data Sources
Currently, Fabric supports mirroring from well-known sources like:
- Azure SQL Database
- Azure Cosmos DB
- Snowflake
- More sources are continuously added by Microsoft
Step-by-Step Guide: Setting Up Data Mirroring in Fabric
Prerequisites
- Active Microsoft Fabric workspace with allocated capacity.
- Mirroring permissions on both Fabric and source database.
1. Enable Mirroring Features in Fabric
- Open the Fabric Admin Portal.
- Ensure Mirroring is enabled for your workspace.
- Verify your Fabric capacity is active and running.
2. Create a Mirrored Database
- In Fabric, go to Create hub > Mirrored Database.
- Provide a unique, descriptive name.
- Select the mirroring type (Database, Metadata, or Open Mirroring).
- Connect to your source database and pick tables for mirroring, or select all.
3. Configure Mirroring Settings
- Decide which tables to mirror: all or selected.
- Confirm and start the mirroring process.
- Initial data sync usually completes within minutes.
Open Mirroring Setup
- After setup, copy the Landing Zone URL from the mirrored database details.
- Use this URL to push change files programmatically from external apps.
- Fabric automatically merges these changes into Delta tables for immediate queries.
4. Query and Analyze Mirrored Data
Use Fabric tools such as Power BI, SQL analytics, or Spark notebooks to:
- Build reports and dashboards on mirrored data.
- Perform advanced analytics or AI model training without affecting source systems.
5. Monitor and Manage Mirroring
- Access the Mirroring Status dashboard in Fabric.
- Track replication progress, health, and errors.
- Adjust mirroring scope and schedules as requirements evolve.
Best Practices for Effective Data Mirroring in Fabric
- Replicate selectively: Mirror only needed tables to optimize storage and costs.
- Secure data: Implement role-based access controls on mirrored datasets.
- Monitor regularly: Set alerts for replication failures or lags.
- Leverage open Delta Lake format: Benefit from compatibility and future-proof analytics.
Common Use Cases
- Centralized data lakes combining multiple operational systems.
- Real-time business intelligence without source system strain.
- Migration of siloed data into unified Fabric lakehouse environment.
- Custom data onboarding via Open Mirroring APIs.
FAQs About Data Mirroring
How quickly is data updated in mirrored databases? Near real-time updates occur through continuous Change Data Capture (CDC) syncing.
Will mirroring affect my source system’s performance? No. Mirroring is designed for minimal impact by offloading queries to Fabric’s copy.
Conclusion
Data Mirroring in Microsoft Fabric is a strategic solution that enables organizations to unify their data, reduce latency, and accelerate analytics. Leveraging Fabric’s mirroring capabilities simplifies data workflows, enhances governance, and unlocks new insights for smarter business decisions.
Start implementing Data Mirroring in Fabric today to build a modern, efficient, and scalable data estate.
