This new capability extends Microsoft Fabric’s zero-ETL data movement strategy, enabling customers to replicate data from BigQuery into OneLake—securely, efficiently, and in near real-time.
What is Mirroring?
Mirroring in Microsoft Fabric allows customers to replicate their operational and warehouse data sources directly into OneLake without complex ETL pipelines. This ensures data stays fresh and is immediately available for analytics in Fabric through its various AI and BI capabilities.
What is Mirroring for Google BigQuery?
- Seamlessly replicate BigQuery tables into OneLake for unified analytics across sources.
- Query mirrored data directly from Power BI, notebooks, and pipelines—no extra data movement required.
- Maintain near real-time freshness through continuous synchronization.
As organizations increasingly operate in multi-cloud environments, we've observed a strong demand from customers for integrating with BigQuery. Making cross-cloud analytics a reality with minimal complexity.
Mirroring leverages Google BigQuery’s change data capture (CDC) capabilities to continuously replicate data into Microsoft Fabric’s OneLake. Once configured, the system tracks row-level changes and replicates only the deltas, minimizing cost and latency. For tables without primary keys, Mirroring supports insert-only replication with a reseed mechanism that reloads the full table if updates or deletes are detected. Customers can configure replication frequency and selectively mirror specific tables. The feature also supports OPDG (On-Premises Data Gateway), enabling secure, private networking for sensitive workloads. Ensuring compliance with enterprise security policies while maintaining high performance and scalability across diverse data environments.
Why it Matters
- The introduction of Mirroring for Google BigQuery in Microsoft Fabric unlocks significant value for organizations.
- Cross-cloud data operations with minimal setup.
- Near real-time insights, and seamless integration into Fabric's powerful suite of anlaytics and reporting tools.
- Simplified governance with Fabric’s unified workspace and security model.
- Reduced ETL overhead, freeing up internal resources.
What's Next?
Mirroring for Google BigQuery is part of our broader semester plan and will continue to evolve based on your feedback. Our roadmap includes improvements in user experience, monitoring, and performance and scalability. As we progress towards general availability, stay tuned for updates.
To learn more, refer to the What is Mirroring in Fabric? documentation.