Microsoft Fabric has become a solid choice for businesses that want to do more with their data. It connects different data sources, cuts down on manual work, and gets insights to teams faster. Data professionals who used to spend hours on fragmented tools and clunky processes have found real relief here.
Microsoft keeps building on the platform. One recent addition worth noting: SQL Database in Microsoft Fabric. You can now handle transactional database work directly inside Fabric- storing, managing, and querying structured data without setting up separate SQL servers.
This guide covers how to get SQL Database running in Fabric, why it matters, and how it connects to everything else on the platform.
What is SQL Database in Microsoft Fabric?
SQL Database in Microsoft Fabric is essentially a powerful database system built directly into the Fabric platform. It lets you store, organize, and work with structured data using familiar SQL commands without needing to leave the Fabric environment. Think of it as adding traditional database capabilities to Fabric’s analytics toolkit.
These databases automatically handle technical details like security, performance optimization, and high availability, while also instantly replicating your data to a special format that makes AI operations faster. This integration makes building data-driven AI applications simpler and more efficient than juggling multiple separate systems.

What Are the Key Features of SQL Database in Microsoft Fabric?
SQL Database in Microsoft Fabric introduces several powerful capabilities designed to make data management, transactions, and analytics more seamless. Here’s a breakdown of its key features:
1. Integrated SQL Database for Transactions and Analytics
SQL Database in Fabric allows businesses to handle both transactional and analytical workloads in one place. It eliminates the need for external SQL servers, providing a fully managed database experience within Fabric.
2. Easy and Quick Deployment
Creating a SQL Database in Fabric is simple—you just need to enter a name, and it’s ready within seconds. Unlike traditional databases, it doesn’t require complex setup for networking, storage, or compute resources.
3. Automatic Data Replication to SQL Analytics Endpoint
Every transaction done in the SQL Database automatically gets replicated to the SQL Analytics Endpoint. This ensures that the latest data is available for analysis without any manual intervention; hence, reporting in Power BI is seamless.
4. AI-Powered Assistance
Fabric hurls AI-enabled capabilities to the SQL experience. Users get AI-assisted query suggestions, code completions, and conversational assistance via Copilot, making it easier to write and optimize SQL queries.

5. Source Control and Git Integration
SQL Database in Fabric allows users to keep database objects under source control, meaning any changes can be committed to a Git repository. This helps maintain version history and makes it easier to collaborate on database development.
6. Real-Time Data Storage in OneLake
All data in SQL Database is stored in OneLake in near real-time using the open-source Delta format. This makes it instantly accessible across different Fabric services like Lakehouse, Data Warehouses, and Notebooks.
7. Auto-Scaling and Performance Optimization
Fabric automatically scales compute resources based on demand, ensuring optimal performance. It also applies intelligent query processing enhancements and auto-creates missing indexes to improve execution speed.
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8. Built-in Security and Compliance
Security is a core focus, with Microsoft Entra authentication, encryption at rest and in transit, and workspace-level permissions inherited by SQL Database. Private Link support ensures network security; while auditing and compliance features help with data governance.
9. Flexible Pricing with Consumption-Based Billing
SQL Database in Fabric only charges for compute when actively used, with auto-scaling to manage costs. Storage and automatic backups are billed separately, giving businesses control over their expenses.
10. Seamless Power BI Integration
Since Fabric is designed for analytics, SQL Database works effortlessly with Power BI’s default semantic models. This allows users to build reports and dashboards directly from SQL data without needing to move or duplicate data.
Creating and Managing SQL Databases in Fabric: A Step-by-Step Guide
SQL Database in Microsoft Fabric simplifies database creation and management while integrating seamlessly with analytics tools. Here’s a detailed walkthrough of each step, from enabling settings to analyzing data.
1. Enabling Tenant-Level Settings
Before creating a SQL Database, tenant-level settings must be enabled to allow access to the preview feature. This is done through the Admin Portal in Fabric. Once enabled, SQL Database will be available in Fabric, allowing users to create and manage their databases.
- Navigate to Settings > Admin Portal > Tenant Settings
- Locate the SQL Database Preview option and enable it
- Choose whether to enable access for the entire organization or specific security groups

2. Database Creation Process
Creating a SQL Database in Fabric is straightforward and requires minimal setup. Unlike traditional SQL servers, Fabric automates most configurations. After creation, the database will be ready for use. Users can access its settings, connection strings, and permissions directly from the workspace.
- Open Fabric and go to Workspaces > New Item > Store Data > SQL Database Preview
- Enter a database name (e.g., SQL-DB-001) and click Create
- If the database limit is reached, delete an existing database and retry

3. Table Management Techniques
Managing tables within SQL Database is essential for organizing data efficiently. Users can create, modify, and delete tables using SQL queries.
- Create a table using the CREATE TABLE command with appropriate columns and constraints
- Insert data using INSERT INTO statements, ensuring auto-increment for primary keys
- Update and delete records while monitoring replication to the SQL Analytics Endpoint

4. Query Execution Best Practices
Fabric supports SQL queries through multiple interfaces, including SQL Server Management Studio (SSMS) and the built-in SQL Query Editor. Executing queries in the right environment ensures fast performance and accurate data retrieval for analytics and reporting.
- Use SSMS by copying the connection string from the database settings
- Run queries in Power BI by selecting the default semantic model
- Monitor query execution time and optimize using indexes and analytics tools

5. Data Analysis Through SQL Analytics Endpoints
SQL Database in Fabric automatically replicates data to SQL Analytics Endpoint, making it instantly available for reporting and visualization. With this integration, businesses can analyze transactional data in real-time without moving or duplicating datasets.
- Refresh the SQL Analytics Endpoint to verify data synchronization
- Create Power BI reports by managing the default semantic model
- Use SQL queries to analyze data stored in OneLake’s Delta format

Data Integration: Using Dataflow Gen 2 & Pipelines

1. Importing Data Using Dataflow Gen 2
Dataflow Gen 2 in Microsoft Fabric is a powerful way to import data into your SQL database from different sources. This intuitive data integration tool allows you to transform, clean, and shape your data before loading it into your database for high data quality and consistency across your system.
- Connect to multiple data sources, including cloud services, on-premises databases, and files
- Apply transformations using a visual interface with Power Query
- Preview data changes in real-time before committing to the final import

2. Setting Up Data Pipelines for Automated Data Loading
Data pipelines are an automated way to update your SQL database with the most current information on a regular basis. These pipelines can be set to run at certain intervals, ensuring that your data update is up to date without any manual intervention and that your AI applications and reports remain backed by a reliable foundation.
- Design multi-step data movement workflows using the pipeline designer
- Schedule pipeline execution based on business requirements
- Monitor pipeline runs through the built-in dashboard to ensure data reliability
- Configure error handling and notifications for failed pipeline runs

3. Creating and Managing a Date Table for Better Reporting
A well designed date table is a prerequisite for good time-based analysis in your Power BI reports that are connected to your SQL database. The importance of creating a full date table in SQL scripts and how this allows you to do more advanced time intelligence functions and increase your reporting capabilities is featured in the transcript.
- Generate a date table using SQL scripts that include various date attributes
- Include fields like year, quarter, month, week, and day to support different time hierarchies
- Add custom business calendar elements such as fiscal periods or business days
- Create relationships between your fact tables and the date table for time-based analysis
- Implement calculated columns for specialized date calculations to enhance reporting flexibility
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Power BI Integration with SQL Database
1. Connecting SQL Database with Power BI
Microsoft Fabric provides seamless integration between SQL databases and Power BI, creating a unified environment for data storage and visualization. This direct connection eliminates the traditional barriers between data storage and reporting tools, allowing for a more streamlined workflow from data to insights without complex configuration or middleware.
- Access your SQL database directly from Power BI within the same Fabric workspace
- Establish live connections for real-time data analysis without data duplication
- Utilize the optimized connection that leverages both platforms’ native capabilities
- Configure refresh schedules to balance between performance and data currency
2. Managing Semantic Models for Advanced Reporting
Semantic models serve as an abstraction layer between your raw SQL data and your business reports, translating technical database structures into business-friendly concepts. Within Fabric, you can create custom semantic models that perfectly align with your organizational terminology and analytical needs.
- Design semantic models that represent your business entities and relationships
- Create calculated measures and columns using DAX expressions
- Implement role-based security at the semantic model level
- Organize fields into logical folders and hierarchies for intuitive navigation
- Apply formatting and default summarization behaviors for consistent reporting

3. Creating and Visualizing Reports with Real-Time Data
With your SQL database connected and semantic models in place, creating powerful visual reports becomes straightforward. Power BI’s rich visualization capabilities, combined with the real-time data from your SQL database, provide a powerful platform for discovering insights and communicating findings.
- Build interactive dashboards using Power BI’s extensive visualization library
- Implement cross-filtering and drill-through capabilities for exploratory analysis
- Create reports that automatically update as new data enters your SQL database
- Design mobile-friendly layouts for on-the-go access to critical insights
- Share reports securely with stakeholders while maintaining data governance

SQL Database in Microsoft Fabric: Performance Optimization & Security
Microsoft Fabric’s SQL Database is designed for high performance, scalability, and security. It leverages auto-scaling, intelligent query processing, and strong security controls to ensure efficient data management and protection. Here’s how these features work:
1. SQL Database Auto-Scaling and Optimization
SQL Database in Fabric automatically adjusts its compute resources based on usage. This ensures that performance remains stable without requiring manual intervention.
- Auto-scaling dynamically increases or decreases compute capacity based on active queries
- Intelligent query processing optimizes execution plans and automatically creates missing indexes
- Real-time data replication ensures that updates are instantly reflected in the SQL Analytics Endpoint
2. Security Features: Authentication, Encryption, and Governance
Fabric’s SQL Database includes built-in security controls to protect data from unauthorized access. These measures secure both stored and transmitted data.
- Microsoft Entra Authentication ensures only authorized users can access the database
- Data encryption at rest and in transit safeguards sensitive information
- Tenant and workspace-level security settings allow fine-grained access control

3. Backup, Restore, and Compliance Settings
SQL Database in Fabric includes automated backup and restore features, ensuring that data can be recovered if needed. Compliance measures help businesses meet regulatory requirements.
- Automatic backups are retained for seven days for disaster recovery
- Restore points allow users to roll back to a previous state in case of data issues
- Auditing and governance policies help track database changes for compliance

Cost-Effective Pricing Model: Breaking Down the Numbers
SQL Database in Microsoft Fabric follows a flexible and cost-effective pricing model that ensures businesses only pay for the resources they use. The platform eliminates unnecessary costs by offering auto-scaling compute, separate storage billing, and a free usage period for early adopters. Let’s break down the pricing details.
1. Fabric Capacity Units Pricing Structure
Microsoft Fabric uses a capacity-based pricing model, where workloads consume Fabric Capacity Units (CU). This approach helps businesses control costs based on actual usage rather than paying for fixed resources.
- SQL Database in Fabric is a native Fabric workload, meaning it consumes CUs like other Fabric services
- The Fabric SKU Estimator (currently in private preview) helps users assess and select the right capacity plan
- Businesses can allocate resources based on their workload needs, ensuring efficient cost management
2. Pay-Only-When-Active Compute Model Benefits
Unlike traditional databases that require continuous provisioning, SQL Database in Fabric follows a usage-based compute model. This means businesses only pay for compute when the database is actively used.
- Compute charges apply only during active queries or transactions
- Auto-scaling adjusts compute power dynamically, reducing unnecessary costs
- Idle databases do not consume compute resources, minimizing expenses during low activity
3. Separate Billing for Storage and Backups
Microsoft Fabric follows a separate billing approach for storage and backups, making it easier to manage costs independently from compute usage. By decoupling storage and compute pricing, Fabric allows businesses to scale each component independently, ensuring a cost-efficient data management strategy.
- Storage is billed monthly, based on the amount of data stored
- Backups are retained for seven days and incur a separate charge after the free period
- Businesses can control costs by managing data retention policies
Advanced Capabilities and AI Readiness
SQL Database in Microsoft Fabric is designed for more than standard data storage and reporting. It is built to support AI-focused use cases from day one. With built-in AI tools, automation features, and tight links to analytics services, Fabric helps organizations grow their data workloads in a smooth and cost-effective way. Below is how it supports AI-based scenarios today and why it is well-positioned for what comes next.
How SQL Database in Fabric Supports AI-Based Applications
As demand grows for AI-driven reporting, forecasting, and automation, SQL Database in Fabric makes sure structured data is always ready for use. Its close connection with the wider Fabric platform allows teams to use AI features without extra setup or complex configuration.
- Real-time replication keeps data fresh so AI models work with the most up-to-date information, which improves accuracy
- Built-in AI tuning helps streamline data pipelines, lower system load, and shorten model training time
- Shared storage through OneLake lets AI tools work with SQL data and other data types in one place, which simplifies data access across teams
AI-Assisted Queries and Automation
Fabric brings AI support directly into the SQL experience. This helps users create, improve, and run queries with less effort and fewer technical skills. As a result, database work becomes simpler, and more people across the business can work with data confidently.
- Copilot allows users to write and adjust SQL queries using plain language prompts
- AI-based query tuning improves performance by suggesting smarter indexes and execution paths
- Automated query execution reduces manual work by adjusting queries to run faster and use fewer resources
Overall, these features help teams spend less time managing queries and more time focusing on results and decisions.
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Real-World Use Cases and Future Roadmap
SQL Database in Fabric is designed to handle various AI-driven business needs, from predictive analytics to real-time data processing. Several industries can benefit from its AI-ready capabilities. Looking ahead, Microsoft plans to expand Fabric’s AI capabilities, making SQL Database even more autonomous, intelligent, and seamlessly integrated with AI-driven automation and analytics.
- Retail & E-commerce: AI-driven demand forecasting and personalized product recommendations based on transactional SQL data
- Finance & Banking: Fraud detection and risk analysis using AI models trained on real-time replicated SQL data
- Healthcare: AI-powered patient data analysis and decision support systems leveraging Fabric’s unified analytics
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As a certified Microsoft Data and AI Solutions Partner, we leverage Microsoft Fabric and Power BI to build scalable, high-performance analytics solutions that streamline data operations, enhance decision-making, and drive business growth.
With numerous successful Fabric deployments (read about our latest successful Microsoft Fabric implementation HERE), we have helped organizations across industries achieve significant ROI by transforming their data into actionable intelligence. Our expertise ensures that your business not only overcomes data challenges but also maximizes efficiency, scalability, and innovation.

Whether you need real-time analytics, AI-powered insights, or seamless data integration, Kanerika delivers tailored solutions that optimize your data strategy and fuel digital transformation.
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Frequently Asked Questions
What is the SQL Database for Fabric?
SQL Database in Microsoft Fabric is a fully managed transactional database designed for structured data storage and real-time analytics. It automatically replicates data to the SQL Analytics Endpoint, allowing businesses to perform both transactions and analytics within Fabric without needing external SQL servers.
Does Microsoft Fabric Use SQL?
Yes, Microsoft Fabric natively supports SQL for both transactional and analytical workloads. Users can create, query, and manage SQL databases directly within Fabric using SQL Server Management Studio (SSMS), Power BI, and Fabric’s built-in query editor, making it an all-in-one data management solution.
How to Create a SQL Database in Fabric?
To create a SQL Database in Fabric:
- Navigate to Workspaces > New Item > Store Data > SQL Database Preview
- Enter a database name and click Create
- Once created, access it through Fabric’s SQL query editor or SSMS
How does SQL Database in Fabric handle data replication?
Fabric automatically replicates data in real-time from SQL Database to the SQL Analytics Endpoint using OneLake’s Delta format. This ensures that any inserts, updates, or deletes in SQL Database are instantly available for analytics.
What are the benefits of using SQL Database in Fabric?
- Built-in AI-powered query assistance
- Auto-scaling compute for cost efficiency
- Seamless Power BI integration for real-time reporting
- End-to-end security with authentication and encryption
How secure is SQL Database in Fabric?
It includes Microsoft Entra authentication, encryption at rest and in transit, private link support, and automatic security updates to ensure data integrity and compliance.


