How to Bring Operational and Analytical SQL Workloads Together in Fabric
You can use Fabric to bring operational and analytical SQL workloads together. This works by using real-time data replication and unified analytics. Fabric Mirroring lets you copy data right away from your operational databases into OneLake. This gives you one place to ask questions, study, and keep your data.
Here are some common reasons and benefits:
You also get a SQL endpoint that makes querying easy. You can make your data storage process simpler too. When you plan your integration, think about the technical upgrades. Also, think about the business value you can get.
Key Takeaways
Fabric helps you put together operational and analytical SQL workloads. This makes data management easier.
Real-time mirroring keeps your data fresh. You can get analytics right away. This helps you make better choices.
Make clear goals first. Check your databases before you use Fabric. This helps everything go smoothly.
Use Fabric’s automatic optimization tools. These tools make queries faster. You do not need to tune them yourself.
Set up strong security steps. Watch performance often. This keeps your data safe and working well.
Fabric Features
Fabric has strong tools to help you connect your operational and analytical SQL workloads. You can use real-time mirroring, OneLake integration, and automatic optimization. These features make your data platform better and easier to use.
Real-Time Mirroring
Fabric Mirroring keeps your data up to date. It copies data from your operational databases into OneLake right away. You do not need to build hard ETL jobs. Your analytics tools always get the newest data.
You always have new data to use.
Both operational and analytical systems work with current records.
Built-in analytics tools read mirrored data for quick choices.
OneLake Integration
OneLake is a single place for all your data. You can store information in standard formats. You use Microsoft Entra to keep access safe and controlled.
Tip: OneLake helps you handle data from many places. You can keep your data safe and neat.
Automated Optimization
Fabric makes your queries run faster. You do not need to tune them yourself. The system builds indexes, saves results, and uses smart joins.
Materialized views save common results for quick use.
Caching keeps answers ready for you.
Predicate pushdown and broadcast joins help with big tables.
You can make your ETL process easier and keep your workloads running well. Fabric lets you manage both operational and analytical SQL workloads in one place.
Planning Integration
Assess Workloads
First, look at your data systems. Find out which databases you use every day. Also, see which ones help with analytics. Make a list of all your databases. Check how you use each database. Decide which ones to move or connect to Fabric.
Tip: Check your licensing and how much capacity you have. Fabric uses capacity-based licensing. Make sure you have enough resources for your needs.
Set up role-based access controls before you start. This helps you follow company data rules. It also keeps your information safe.
Checklist for Assessment:
List all operational and analytical databases.
Write down how you use each database.
Check licensing and capacity.
Set up security controls.
Define Goals
Think about what you want from integration. Do you want faster analytics? Do you want one platform for all your data? Write down your main goals.
You might want to:
Get better performance for analytics.
Make your data setup simpler.
Make data easier to manage and keep safe.
Clear goals help you pick the right tools. They also help you measure success later.
Choose Components
Pick the best Fabric parts for your needs.
Use the SQL database in Fabric for operational workloads. It works well for transactional data. It can scale up by itself.
Choose Fabric Warehouse for analytics workloads. It is good for structured data. It helps with business intelligence tasks.
You can bring operational and analytical SQL workloads together. Match each workload to the right Fabric part. This makes your data platform strong and flexible.
Integration Steps
Bringing your operational and analytical SQL workloads together in Fabric takes a few key steps. Each step helps you move data and get real-time analytics. Use this guide to make your integration easy and successful.
Prepare Data
First, get your data ready to move. Look at your databases and see if they work with Fabric. Make sure your source databases, like Azure SQL Database or on-premises SQL Server, are updated and easy to reach.
Clean your data. Remove copies and fix mistakes.
Check if tables have primary keys and indexes.
Back up your databases before you begin.
Make a login and user in SQL Server using SQL Server Management Studio (SSMS).
Tip: Checking your current setup helps you plan better. You can save money and work faster by removing things you do not need.
Set Up Mirroring
Set up mirroring to keep your data matched between systems. Mirroring copies your data right away from your source database to OneLake in Fabric. This makes sure your analytics always use the newest data.
Follow these steps to set up mirroring:
Check if your Azure SQL Database meets all needs.
Use SSMS to make a login and user for Fabric.
Create a Connection in Fabric
Go to Settings > Manage Connections and Gateways in Fabric.
Add a new connection with your SQL Server info.
Set Up the Mirrored Azure SQL Database
In your Fabric workspace, pick New Item > Mirror Azure SQL Database.
Choose your connection and pick the tables to mirror.
Name your mirrored database and click Create.
Mirroring means you do not need hard ETL jobs. Your data stays fresh, and you can use it for analytics right away.
Migrate Workloads
Now move your workloads to Fabric. Migration means moving your data and work from your old system to the new one. Good planning helps you avoid problems.
Groups with a clear cloud plan move better.
A strong business reason helps you reach your goals.
If your plan is not clear, people may not agree.
Getting everyone on board helps the move go well.
Note: Planning for the future helps you get ready for new tech and business needs.
Enable Analytics
After mirroring and moving workloads, you can turn on analytics for your operational and analytical SQL workloads. Fabric lets you run fast queries on mirrored data. You do not need to move or copy your data.
Analytics tools like Azure SQL, Databricks, and Dataverse connect to mirrored data for almost real-time access.
Direct Lake mode lets you ask questions on data in Delta Lake format in OneLake.
You get quick, current reports on your operational data.
With Fabric, you get instant answers and make smarter choices. Real-time analytics help you act fast when your business changes.
Optimize and Avoid Pitfalls
When you use Fabric for both operational and analytical SQL workloads, you must keep things running well and safe. Follow these steps to get good results and avoid mistakes.
Tune Performance
Fabric has tools that help your system work faster. These tools make your queries quicker and keep your data neat.
Use the
VACUUMcommand to clear out old files. This saves space and helps your system run better.The
OPTIMIZEcommand puts small files together into bigger ones. This makes your queries finish faster.V-order optimization changes how data is stored. This makes searching faster and uses less input/output.
Deletion vectors help you remove old data quickly.
Pre-warm the Direct Lake cache so your most-used data loads faster.
Tip: After you connect your workloads, queries can run up to 33% faster. You may also spend two to three times less than with old systems.
Secure Data
Keeping your data safe is very important when you use Fabric. There are many ways to protect your data.
Set up Azure Private Link to keep access inside your network. This blocks outside internet connections.
Give users only the access they need by using roles. This follows the least privilege rule.
Use sensitivity labels from Microsoft Purview Information Protection. These labels help you mark and protect important data.
Note: Always check your security settings before and after you move your data. This keeps your SQL workloads safe.
Monitor and Troubleshoot
Watching your system helps you find problems early. Fabric gives you tools to help you do this.
Use performance tools to find and fix slow spots.
The Microsoft Fabric Capacity Metrics app shows how much database space you use.
The Performance Dashboard gives you a full view of your databases.
Query Dynamic Management Views (DMVs) with T-SQL to learn about memory, blocking, and deadlocks.
Track input/output events and DWU usage with SQL Streaming widgets.
Built-in monitors show health and performance signals. Forecast monitors help you plan for what you will need later.
Remember: Stay away from these mistakes to make your integration easy and successful.
Operational and Analytical SQL Workloads in Fabric
Unified Platform Benefits
Fabric lets you handle both operational and analytical SQL workloads together. You do not need different systems for OLTP and OLAP. This makes your work easier and saves time. You also spend less money because you move data less. Teams can work better since everyone uses the same data. Fabric helps break down data silos. You get access to all your data sources easily. Teams share one main set of data, so teamwork improves. Real-time analytics help you make quick choices for your business. Central rules keep your data safe and managed. You use fewer tools, so your work is simpler. Everyone works in the same place, no matter their skill level. You get instant insights from new data. You can find information faster and make smarter decisions.
Fabric Databases mix OLTP and OLAP features. You can make fast choices and also look at details. You can update old systems to new ones. First, get your environment ready. Next, plan how you will move your data. Then, change your pipelines to work with Fabric. Last, stop using old systems. The medallion architecture helps you organize data in layers. This makes things clearer and more efficient.
Real-Time Insights
Fabric lets you mirror your operational databases. Your data stays matched almost right away. You always have the newest information for analytics and AI. You can use tools like Striim to move data from SQL Server or cloud sources into Fabric. In-memory processing and special connectors make this fast and reliable.
Here is how you get real-time insights:
Mirror your Azure SQL Database in Fabric for easy replication.
Keep your data synchronized in near-real time.
Store your data in Delta tables in OneLake for efficient management.
Use analytics and AI tools to act on fresh data.
When you use Fabric for both operational and analytical SQL workloads, you get instant analytics and can make smarter business choices.
You can use Fabric to connect your operational and analytical SQL workloads. Real-time mirroring helps keep your data up to date. When data is unified, teams can work together more easily. Regular optimization makes things run faster. Try starting with a small project to see how things work. Use tools like Eventstreams and Real-Time Dashboards to get quick insights.
Check out learning resources to improve your skills. Stay informed about new features like DOP Feedback and Power BI Desktop connections.
Keep learning and look for updates so you can use Fabric better.
FAQ
How do you start mirroring your operational database in Fabric?
First, connect your source database to Fabric. Go to the Fabric portal and set up mirroring. Pick the tables you want to mirror. Follow the steps shown to finish the setup.
Can you use Fabric for both cloud and on-premises SQL databases?
Yes, you can use Fabric for both types. Fabric works with Azure SQL Database and on-premises SQL Server. Use connectors or tools like Striim to move your data into Fabric.
What tools help you monitor performance in Fabric?
You can use the Microsoft Fabric Capacity Metrics app. The Performance Dashboard shows all your workloads. Query Dynamic Management Views (DMVs) for more details.
How do you keep your data secure in Fabric?
Set up role-based access controls for users. Use Microsoft Entra to check who can log in. Add sensitivity labels to protect important data. Always check your security settings after you move your data.
What should you do if you see slow queries after migration?
Look at your indexing and use the
OPTIMIZEcommand. Check query plans for slow spots. Use built-in tools to find and fix problems fast.