Introduction
- As data piles up and companies need insights faster than ever, it’s critical to ensure that your data is always accurate, easy to access, and ready to be analysed.
- That’s where Microsoft Fabric comes in—it’s a powerful platform that simplifies data management and analytics, making it easier to stay on top of things.
- This basically keeps your analytical environment perfectly synced with your operational data sources, and it happens in real time. So, no more worrying about your data being out of date when you’re trying to pull reports or make decisions.
- In this post, we’ll break down how database mirroring works in Microsoft Fabric, the benefits it offers, the supported data sources, its limitations, and some smart strategies for using this tech to keep your analytics fresh, accurate, and ready to go when you need them.
Mirroring in Fabric: An Overview
What is Mirroring in Fabric?
- In Microsoft Fabric, mirroring is all about keeping your data synced up in near real-time. It continuously pulls data from various sources and updates it in Fabric’s One Lake, so you always have the freshest information at your fingertips.
- Unlike traditional ETL processes, which usually involve loading data on a set schedule, mirroring keeps everything up to date automatically. That means no more complex pipelines or worrying about data getting stale.
- It also works seamlessly with native cloud sources, like Azure SQL Database, and you can even connect it to custom sources through Open Mirroring.
Why Mirroring Matters
Why Use Mirroring?
- Real-time updates: Your analytics are always based on the latest operational data.
- Minimized manual effort: No complex data movement or ETL maintenance required.
- Cost efficiency: Reduce data movement overhead and infrastructure needs.
- Flexible data integration: Easily connect cloud, on-premises, or custom data sources.
- Use Cases: Real-time reporting, compliance dashboards, unified data analysis, multi-branch/store syncing.
Mirroring Workflow
How Does Mirroring Work?
Mirroring in Microsoft Fabric is designed to provide seamless, near real-time synchronization of data from source systems into Fabric’s unified analytics lake—One Lake—enabling immediate analytics without traditional delays.
Step 1: Connection Setup
- The first step is to establish a connection between your operational data source and Microsoft Fabric. Fabric supports native connectors for popular cloud databases such as Azure SQL Database, and through Open Mirroring, you can also connect custom or legacy sources by pushing data in standard formats like Parquet or CSV.
Step 2: Selecting Data to Mirror
- You can choose to mirror entire databases or selective tables and columns depending on your analytic requirements. This flexibility allows you to avoid unnecessary data duplication and focus on the most critical data for your scenarios.
Step 3: Mirroring Modes
- Microsoft Fabric offers multiple mirroring modes tailored to different needs:
Native Mirroring:
- This mode establishes a direct, secure connection to supported sources and performs full data replication including inserts, updates, and deletes, ensuring mirror data is an exact reflection of the source.
Shortcut Mirroring:
- Rather than copying all data, this mode mirrors metadata like schema and table definitions while referencing the original data in place. Queries run via shortcuts access the latest source data dynamically, which is ideal for very large datasets or when you want to minimize storage.
Open Mirroring:
- For data sources without native connectors, Open Mirroring enables you to push incremental change data files in formats like Parquet or CSV to Fabric. Fabric processes these files to keep mirrored tables updated.
Step 4: Continuous Synchronization
- Once mirroring is enabled, Fabric continuously listens for changes (also called change data capture) in your source systems and replicates them to One Lake with minimal latency.
- This near real-time sync guarantees your analytics dashboards and reports are always based on fresh data.
Step 5: Monitoring and Management
- Fabric provides built-in tools within its workspace to monitor mirroring health, synchronization status, and error logs.
- If the source system goes offline temporarily, Fabric automatically resumes syncing when the connection is restored, providing robust fault tolerance.
Step 6: Security and Compliance
- All mirroring communications are encrypted in transit and data at rest in One Lake is secured according to Microsoft’s enterprise-grade compliance standards, ensuring sensitive information always remains protected.
Supported Data Sources for Mirrored Database
Native Mirroring
- Azure SQL Database
- Azure SQL Managed Instance
- Azure Cosmos DB
- Snowflake
SQL Server (Preview)
- SQL Server 2016–2022 (Windows/Linux)
- SQL Server 2025 (on-premises)
Open Mirroring (via Partner Tools)
- Oracle (via GoldenGate 23ai)
- MongoDB Atlas
- SAP (dab Nexus, SNP Glue, Simplement, ASAPIO, Theobald)
- Striim (supports multiple enterprise sources like Oracle & SQL Server)
- CluedIn (Master Data Management)
Cons / Limitations of Mirroring in Fabric
Even though mirroring is powerful, it comes with some trade-offs:
- Source Limitations – Works only with supported systems; others need Open Mirroring or third-party tools.
- All-or-Nothing Table Sync – You can’t mirror specific columns, only full tables.
- Performance Impact on Source – Continuous Change Data Capture (CDC) may put extra load on the source database.
- On-Premises Dependency – Private/on-prem sources require a reliable gateway, which can be a single point of failure.
- Preview Features – SQL Server mirroring is still in preview; functionality and billing may change.
- Security Gaps – Column/row-level permissions from the source are not automatically enforced in Fabric.
- No Row Filtering – Entire tables are mirrored, without custom row-based filters.
Setting Up Mirroring in Fabric: A Quick Guide
- Ensure you have the right permissions and know your data source details.
- Go to the Fabric workspace and select “Mirrored Database” under data pipelines.
- Choose your data source and provide connection/configuration details.
- Select tables (or whole databases) to mirror.
- Review options (native, shortcut, open mirroring) and configure as needed.
- Start mirroring—Fabric will handle the rest!
- Monitor and manage from the Fabric UI.
Best Practices for Using Mirroring
- Start with small datasets to validate your pipeline.
- Use native mirroring where possible for maximum automation.
- For large or infrequently changing data, consider shortcut or open mirroring to save storage.
- Regularly check synchronization status and error logs.
- Document your mirroring setup for compliance and troubleshooting.
Key Use Cases and Real-World Examples
- A retail company mirrors sales data from each branch to enable real-time dashboard updates.
- A financial services firm syncs transactions to support up-to-the-minute risk monitoring.
- Healthcare providers mirror patient records to analyse trends and ensure compliance with data retention laws.
Conclusion
Mirroring in Microsoft Fabric empowers organizations with always-fresh, reliable analytics while removing the complexity of manual data movement. Whether you need real-time dashboards, compliance reporting, or a unified analytics platform, mirroring delivers the data agility required by modern businesses. Start exploring mirroring in Fabric today to streamline your journey from data to insight.
