Announcing Staging for Mirroring for Google BigQuery (Preview)

Microsoft Fabric Blog introduces staging support for Mirroring Google BigQuery, explaining how this enhancement boosts replication speed and reliability for data engineers and analytics teams.

Announcing Staging for Mirroring for Google BigQuery (Preview)

The Microsoft Fabric team has released a significant update: staging support for Mirroring Google BigQuery datasets (in Preview). This enhancement dramatically accelerates initial data replication into Microsoft Fabric, optimizing analytics and cross-cloud data scenarios.

Why Staging Matters

Historically, importing large datasets from BigQuery into Fabric could be slow. With staging enabled, organizations report over 90% performance improvements for the initial sync. For instance, 1.5 TB of data (over 6 billion rows) can now be replicated in 50 minutes instead of taking days.

How Staging Works

Staging introduces an intermediate data layer that:

• Optimizes throughput for large-scale, bulk data ingestion
• Reduces latency for first-time connections
• Increases reliability by reducing errors during large transfers

Benefits for Analytics

• Fast analytics access: Teams can quickly analyze BigQuery data in Fabric
• Streamlined workflows: Reduces or eliminates the need for complex ETL pipelines
• Reliable cross-cloud analytics: Improves trust in data replication and integration

Try It Out

Getting started is simple:

• Mirroring Google BigQuery in Microsoft Fabric (Preview)
• Tutorial: Set Up Mirroring for Google BigQuery (Preview)

Conclusion

This enhancement meets the growing need for fast, scalable analytics and robust cross-cloud data engineering, with native support for BigQuery-to-Fabric scenarios.

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