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.
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 This allows businesses to make decisions based on the most current situation, rather than relying on outdated information.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.
Learn more about Mirroring
- Tutorial Mirroring Azure SQLDB in Fabric
- Blog: Mirroring for Azure SQL Database in Fabric
- Blog: GA Announcement of Mirroring Snowflake in Fabric
- Mirroring for Cosmos DB in Fabric
- Get Started with a Fabric free trial
- Share feedback, ideas or suggest new features for Mirroring Azure SQLDB
We hope you enjoy using Mirroring Azure SQL Database in Fabric and we look forward to hearing your feedback and questions.
