Microsoft Fabric Rolls Out Database Mirroring Preview
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Microsoft Fabric
Mar 26, 2024 11:00 PM

Microsoft Fabric Rolls Out Database Mirroring Preview

by HubSite 365 about Microsoft

Software Development Redmond, Washington

Data AnalyticsMicrosoft FabricM365 Release

Explore the public preview of Database Mirroring in Microsoft Fabric for real-time data insights & AI integration.

Key insights


  • Public Preview of Database Mirroring in Microsoft Fabric is now available.
  • Mirroring was first announced at Ignite in November 2023.
  • Enables seamless integration of databases into OneLake in Microsoft Fabric.
  • Provides zero-ETL, near real-time insights on data.
  • Unlocks capabilities in warehousing, BI, AI, and more.

Mirroring in Microsoft Fabric

Microsoft Fabric's latest offering, the Public Preview of Database Mirroring, is a game-changer for businesses seeking to consolidate and analyze their data more efficiently. This feature simplifies the process of integrating various databases with OneLake, Microsoft Fabric's data lake solution, bypassing traditional ETL (Extract, Transform, Load) complexities.

Now, organizations can achieve near real-time insights, significantly speeding up decision-making processes and enhancing business intelligence capabilities. The initiative, which was first announced at Microsoft's Ignite event in 2023, reflects Microsoft’s commitment to enhancing data accessibility and analytics. It opens up new avenues for warehousing, Business Intelligence (BI), Artificial Intelligence (AI), and more, promising an integrated and streamlined approach to data management.


Read the full article Announcing the Public Preview of Database Mirroring in Microsoft Fabric



Introducing Database Mirroring in Microsoft Fabric

We're thrilled to announce the Public Preview of Database Mirroring in Microsoft Fabric. This feature, first revealed at Ignite in November 2023, is now accessible for customers. It allows for the effortless integration of databases into OneLake within Microsoft Fabric.

This integration facilitates seamless, zero-ETL, and near real-time data insights. It opens doors to warehousing, BI, AI, and more, enhancing your data management and analysis capabilities.

  • Public Preview of Database Mirroring now available
  • Seamless integration of databases into OneLake
  • Enables zero-ETL, near real-time insights
  • Facilitates warehousing, BI, AI, and more

People also ask

Is database mirroring deprecated?

Based on the information provided by Microsoft, the technology of database mirroring is on its way to being phased out in forthcoming versions of SQL Server. Users are encouraged to transition towards utilizing Always On availability groups. Database mirroring functionalities have traditionally been divided among three SQL server roles: the principal server hosting the primary database for read/write operations, the mirror, and the witness.

What are the disadvantages of database mirroring?

Database mirroring faces limitations such as its restriction to the database level, excluding server-level integration. This means it only forwards changes made within the database itself, leaving server-level elements like logins and fixed server role memberships unaffected. Moreover, its automated server failover system may not align well with applications that depend on multiple databases.

What are the prerequisites for database mirroring?

Setting up database mirroring requires a few initial steps: both the principal and mirror servers must be configured to allow remote access, and they should have identical permissions. Additionally, establishing a witness server is necessary for overseeing the operations of the principal server.

What is mirroring in fabric?

Mirroring takes advantage of the database's Change Data Capture technology to convert information into Delta tables which are then integrated into OneLake. This process facilitates the merging of data across various databases, providing the capability to carry out queries over any combination of databases, warehouses, or lakehouses.



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