Microsoft Fabric Updates Blog

Mirroring Azure SQLDB – new features and what’s coming up?

Overview

This blog will walk thru the new capabilities in Mirroring Azure SQLDB in Fabric since our public preview announcement earlier in March 2024. Today, we also announced general availability of Mirroring for Snowflake in Microsoft Fabric.

To recap, the 3 key benefits of Mirroring are:

Reduced total cost of ownership with zero compute to replicate along with generous amounts (terabytes) of storage based on the capacity size.
Zero code with zero ETL.
Faster time to operational data, information to derive insights.

Over the past few months, we’ve removed limitations to seamlessly support more data definition language (DDL) when Mirroring is actively running. These DDL’s are:

Alter Table … Alter Column to change one datatype to another
Drop Table
Rename Table
Rename Column

The following demo video below will walk thru how Mirroring in Azure SQL Database works with the new features mentioned above.

Mirroring Azure SQL Database in Fabric with Schema changes

Use Cases

Below are some of the key use cases that leverages Mirroring:

Data is replicated into One Lake and kept up to date in near real-time.
Mirroring protects operational databases from analytical workloads.
Raw data available in Fabric Lakehouse as a bronze layer to enable Medallion architecture.
Leverage Direct Lake mode in Power BI instead of Direct Query or import mode.

What’s coming up in future milestone release for Mirroring Azure SQLDB

We’ve heard your feedback loud and clear and are heads down working on some of your key asks. The features below are coming soon in an upcoming milestone release:

Allow connectivity to SQL Databases behind firewall or private endpoints using Vnets
Ability to setup and manage Mirroring using programmatic APIs
Support for schema hierarchy and column mapping in data warehouse and lakehouse experiences
Mirror tables with no defined primary keys
Security improvements to connect SQLDB with lower level/reduced SQL permissions
Mirror additional data types (sql_variant, geography, geometry etc) to Fabric OneLake
Support for DDL: Truncate Table

Summary

Mirroring Azure SQL Database in Fabric plays a crucial role in enabling analytics and driving insights from data by providing:

Timeliness of Insights: Ensuring the most recent data is available for analysis. This allows businesses to make decisions based on the most current situation, rather than relying on outdated information.
Improved Accuracy: The risk of discrepancies between the source and the replicated data is significantly reduced leading to more accurate analytics and reliable insights.
Predictive Analytics and AI: Essential for data science, machine learning and AI models that require the most recent data to make accurate predictions for data based decisions.