One SQL Anywhere - Designing Scalable Data Solutions with Microsoft Fabric

[rajendraongole1]

If you have been working with Microsoft Fabric for a while, you know the ecosystem keeps growing. One of the most exciting pieces to land recently is SQL Database in Fabric—and it is now generally available. It brings the familiarity of T-SQL directly into your Fabric workspace, automatic mirroring to OneLake, and—this is the part that surprised me—native support for vector embeddings and semantic search, all without leaving your SQL editor.

This is the first post in a practical series where we will explore how SQL databases work inside Microsoft Fabric by building and testing everything step by step inside a Fabric workspace.

In this part, I will cover the following:

1. Creating a SQL Database in Fabric and loading sample data
2. Writing and running real T-SQL queries
3. Exploring the SQL Analytics Endpoint and understanding OneLake replication

By the end of this post, you will have a working database inside your Fabric workspace and a clearer understanding of how all these components connect together. Let us dive in.

Environment Setup

Before we create a database, we need a Fabric workspace to put it in. If you already have one set up, you can skip ahead to Section 2. Otherwise, follow these steps.

Step 1: Create a New Fabric Workspace
A workspace in Microsoft Fabric is your working area — think of it like a project folder that holds all your items: databases, lakehouses, reports, pipelines, and more.

1. Go to app.fabric.microsoft.com and sign in with your Microsoft account.
2. On the left navigation panel, click Workspaces, then click New workspace.
3. Give your workspace a clear name — for example, FabricSQLLab or SQLFabricPart1.
4. Under Advanced settings, make sure the license mode is set to Fabric capacity (you need at least F2 for SQL Database).
5. Click Apply to create the workspace. You will land inside it automatically.

Tip: If you do not see a Fabric capacity option, talk to your tenant admin. An SQL database in Fabric requires Fabric-enabled capacity—it does not run on Power BI Premium P-SKUs alone.

Step 2: Create a SQL Database in Microsoft Fabric
Now that the workspace is ready, let us create the database.

1. Inside your workspace, click New item (the + button near the top of the page).
2. Scroll down to the Databases section and select SQL database.
3. Give it a name — something like SQLDBDemo works well for this series.
4.Click Create. Fabric provides the database automatically. This usually takes under a minute.

When the database is ready, you will land on its home page. You will notice a few things right away:

The Database Explorer panel on the left shows your schemas, tables, and views in a tree structure
The SQL query editor in the center—this is where you write and run T-SQL
The Replication tab at the top tracks how your data is being mirrored to OneLake

Tip: Everything you create in this SQL database is automatically backed by OneLake storage in Delta Parquet format. You do not need to set up any pipelines or export processes—it happens in the background.

Step 3: Load the Database with sample data.
Fabric makes it easy to get sample data loaded so you can start working right away. The SalesLT dataset is a lightweight sales database with customers, products, orders, and addresses—perfect for practicing T-SQL.

1. On the database home page, look for the Sample data option—it is usually shown as a quick action or under the Settings menu.
2. Select "Load sample data" and choose "SalesLT."
3. Wait for the loading process to complete. A progress bar will show the status.
4. Once done, look at the Database Explorer panel on the left. Click the dropdown arrow next to your database name to expand it.
5. You should see the SalesLT schema listed, with tables like Customer, Product, ProductCategory, Address, and SalesOrderHeader underneath.

Tip: Expand SalesLT in the database explorer. If you see tables like Customer, Product, and SalesOrderHeader listed—you are good to go. If the schema is empty, wait a moment and refresh the page.

Now open a new query window that we will use to work directly with the database. Copy and paste the following code into the query window:

SELECT * FROM [SalesLT]. [ProductCategory]

Exploring the SQL Analytics Endpoint

Here is something that makes SQL Database in Fabric different from a regular managed database: it automatically replicates your data to OneLake. This means other Fabric workloads—Spark notebooks, Power BI reports, and Eventstreams—can all read your SQL data without you having to move or copy it.
The SQL Analytics Endpoint is the read-only T-SQL interface to your replicated OneLake data. Think of it as a second door into the same data, optimized for analytics rather than transactions.

Tip: The SQL Analytics Endpoint is what Power BI connects to when you create a semantic model on top of your Fabric SQL data. It is also what you would use for heavy analytical queries—large aggregations, GROUP BY operations, and window functions—without putting load on the transactional database.

Monitor Replication Status

1. On your database home page, click the Replication tab at the top left of the page.
2. Select "Monitor replication" from the dropdown.
3. You will see a panel showing the replication status—which tables have been mirrored, the last sync time, and any errors that exist.
4. If replication is running correctly, all your SalesLT tables should show a green status with a recent timestamp.
5. Close the Monitor Replication pane by clicking the X icon when you are done.

Tip: What is happening in the background? Every time you insert, update, or delete rows in your SQL database, those changes are automatically captured and written to OneLake in Delta Parquet format. This is the same format that Spark, Power BI Direct Lake, and other Fabric engines read natively — so there is no ETL process needed.

Once you select mirror replication:

What We Covered in Part 1
In this post, we went step by step through setting up and exploring SQL databases in Microsoft Fabric. Here is a quick summary of what we completed:

1. Created a Fabric workspace and configured the required capacity
2. Created a SQL Database in Fabric without worrying about server setup or firewall configuration
3. Loaded the AdventureWorksLT sample dataset and explored the tables using Database Explorer
4. Ran T-SQL queries directly inside the Fabric SQL editor, including basic queries and JOIN operations
5. Checked the Replication tab to see how data is mirrored into OneLake
Opened the SQL Analytics Endpoint to understand how the same data can be used for analytics and reporting

If you have worked with SQL Server or Azure SQL before, the experience will already feel very familiar. That is one of the biggest advantages of SQL Database in Fabric—you continue using the same T-SQL skills and concepts while getting the benefits of the Fabric ecosystem and OneLake integration.

Coming Up in Part 2

In the next part of this series, we will go deeper into working with SQL databases in Fabric by exploring more advanced querying, performance features, and integration scenarios inside the Fabric environment.

Happy Reading!

[Shashi_36]

looks great and insightful @rajendraongole1 sir