Unified data platform with Fabric Databases

Overview of Fabric Databases

Recently in Microsoft Ignite2024, Microsoft announced Fabric Databases, in preview. Fabric Databases introduce a new version of cloud databases, by offering transactional database natively within Microsoft Fabric for app developers. With the inclusion of Fabric Databases, Fabric now unifies both transactional and analytical workloads, creating a comprehensive data platform. Developers can streamline application development with simple, autonomous, and AI-optimized databases that provision in seconds and come secured by default with features like cloud authentication and database encryption.

With use of Copilot in Fabric Developers can translate natural language queries into SQL and can get inline code completion along with code explanations and fixes. The SQL database, the first to be available in Fabric, is built on our top-tier SQL Server engine and Fabric’s user-friendly SaaS platform. Data professionals who have used the SQL database in Fabric have reported completing common database tasks up to 71% faster and with 63% greater effectiveness. They also felt 84% more confident in their tasks and found them up to 91% less difficult.

The SQL database in Fabric is:

1. The hub for OLTP workloads within Fabric
2. Simple to configure and manage
3. Optimized for analytics by automatically replicating data into OneLake in near real-time
4. Integrated with development frameworks and analytics tools
5. Built on the Mirroring technology in Fabric
6. Accessible through the same methods as Azure SQL Database, with an additional web-based editor in the Fabric portal.

When you create a SQL database in Fabric, it generates three items in your Fabric workspace:

1. Data from your SQL database is automatically replicated into OneLake and converted to Parquet, making it ready for analytics.
2. A SQL analytics endpoint
3. A default semantic model

Additional Capabilities:

• Fabric Database enables data professionals to focus on building app: Without complicated configuration selections of networking, compute, and storage requirements, simply provide database name and database is ready to use in seconds.
• For SQL database all your data get replicated in OneLake in near-real time for analytics and AI: All SQL database data resides in OneLake in open-source delta parquet format. With SQL database deployment in Fabric, you get two endpoints: database endpoint and SQL analytics endpoint, which allows querying data from OneLake.
• Billing for SQL database in Fabric capacity model: Compute charges are incurred only when the database is in active use, and the compute resources automatically scale as needed. The SQL database in Fabric will be free until February 1, 2025. After this date, compute and data storage charges will apply, with backup billing commencing on March 1, 2025.
• Fabric SQL databases are autonomous: SQL database in Fabric is automatically configured, Storage and compute scale automatically as per user workload, auto-optimized to improve query performance, security updates with auto-patching, automatic backups are available for Fabric Database.
• Default Security and data governance: Fabric Database comes with default security features like authentication by Microsoft Entra and with TLS 1.2-encryption at rest and in transit. Permissions configured at workspace level are inherited by SQL database. Central data governance with Microsoft Purview allows sensitivity labels and enforcement of Purview data protection policies.
• AI apps with Fabric SQL Database: Developers can enhance application development with easy-to-use, autonomous, and AI-optimized databases that provision in seconds and come with default security features like cloud authentication and database encryption. Built-in vector search, retrieval-augmented generation (RAG) support, and Azure AI integration make AI app development simpler, while your data is immediately accessible in OneLake for advanced analytics.

Data ingestion and querying in Fabric SQL database

Step1: Once you have created Fabric SQL database in workspace, you can populate database in various ways like Dataflow Gen2, data pipeline, T-SQL, external database through connection strings or load it with sample data as shown below.

Step2: Database with populated SalesLT sample data is ready to use.

Step3: Query SQL database using SQL editor

Step4: Insert data using T-SQL

Similarly, you can ingest data into and export out data of Fabric SQL database by using Fabric Data Pipeline. In data pipeline, you can use Dataflow Gen2 with Power Query interface to perform transformations and other operations on the Fabric database data.

Conclusion:

The SQL database is just the start for Fabric Databases, with more options planned in future. The SQL database in Fabric is embracing the principles that have driven Fabric’s rapid growth among enterprises and small businesses. Whether you’re a seasoned data professional or a beginner, you can develop AI apps more quickly and confidently using Fabric Databases. This unified and integrated platform allows you to develop AI apps more quickly and with reduced overhead.

About CloudThat

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