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Mirroring in Fabric offers a simple way to avoid complex ETL (Extract, Transform, Load) processes and seamlessly integrate your existing Google BigQuery warehouse data with the rest of your data in Fabric. You can continuously replicate your Google BigQuery data directly into Fabric's OneLake. Once in Fabric, you can take advantage of powerful capabilities for business intelligence, AI, data engineering, data science, and data sharing.
For a tutorial on configuring your Google BigQuery database for Mirroring in Fabric, see Tutorial: Configure Microsoft Fabric mirrored databases from Google BigQuery.
Important
Mirroring for Google BigQuery is now in preview. Production workloads aren't supported during preview.
Why use mirroring in Fabric?
Mirroring in Microsoft Fabric removes the complexity of stitching together tools from different providers. No need to migrate your data. Connect to your Google BigQuery data in near real-time to use Fabric's array of analytics tools. Fabric also works seamlessly with Microsoft products, Google BigQuery, and a wide range of technologies that support the open-source Delta Lake table format.
What analytics experiences are built in?
Mirroring creates a mirrored database and a SQL analytics endpoint in your Fabric workspace. The mirrored database manages replication of data into OneLake and conversion to Parquet, enabling downstream scenarios like data engineering, data science, and more.
The SQL analytics endpoint provides a read-only analytical experience on top of the Delta tables created during mirroring. You can browse mirrored tables, build no-code queries and views, create SQL views and stored procedures, and query data across warehouses and lakehouses in the same workspace.
For more information on analytics capabilities and compatible tooling, see Mirroring objects.
Security considerations
There are specific user permission requirements to enable Fabric Mirroring.
Fabric also provides data protection features to manage access within Microsoft Fabric. For more information, see our data protection features documentation.
Mirrored BigQuery cost considerations
The Fabric compute used to replicate your data into Fabric OneLake is free. The Mirroring storage cost is free up to a limit based on capacity. The compute for querying data using SQL, Power BI, or Spark is charged at regular rates.
Fabric doesn't charge for network data ingress fees into OneLake for Mirroring.
There are Google BigQuery compute and cloud query costs when data is being mirrored: BigQuery Change Data Capture (CDC) utilizes BigQuery compute for row modification, Storage Write API for data ingestion, BigQuery storage for data storage that all incurs costs.
For more information on costs for mirroring Google BigQuery, see the pricing explained.