Azure Data Studio vs SSMS: A Comparison of SQL Management

Azure Data Studio and SSMS are two popular tools for managing SQL databases. Azure Data Studio is a cross-platform tool that allows users to connect to SQL Server, Azure SQL Database, and other data sources.

One key difference between the two tools is that Azure Data Studio is designed to be more extensible than SSMS. This means that users can add custom extensions to enhance its functionality.

Azure Data Studio is also more lightweight than SSMS, requiring fewer system resources to run. This makes it a good option for users who need to manage databases on lower-end hardware.

To use Azure Data Studio, you'll need a 64-bit operating system, preferably Windows 10 or later, with at least 4 GB of RAM and 2 GB of free disk space.

Azure Data Studio supports a wide range of database management systems, including SQL Server, Azure SQL Database, and PostgreSQL.

You'll need to install the .NET Framework 4.7.2 or later for Azure Data Studio to run smoothly.

Azure Data Studio is compatible with both 32-bit and 64-bit versions of Windows, but 64-bit is recommended.

SSMS requires Windows 7 or later, with at least 2 GB of RAM and 1 GB of free disk space.

SSMS supports a limited number of database management systems, primarily SQL Server and Azure SQL Database.

Azure Data Studio has a solid foundation in Microsoft's Visual Studio Code source code editor, making it a powerful tool for database management.

It includes an integrated terminal window that allows users to execute database management commands with Bash, PowerShell, sqlcmd, and other command-line tools from within the UI.

Azure Data Studio also offers a T-SQL editor with features like smart code navigation and integration with Git for tracking source code.

Users can save query results as text, JSON, or Excel files, and the editor supports creating stored procedures, scripts, and other database objects.

The tool provides a set of T-SQL code snippets to streamline writing T-SQL statements, including templates for creating new databases, tables, and views.

Azure Data Studio also allows users to create custom code snippets for actions not covered by the built-in ones.

It supports SQL Server from 2014 to 2019 preview, as well as Azure SQL Database and Azure SQL Data Warehouse, with preview support for Azure SQL Database Managed Instance.

Importing and exporting data is a crucial aspect of working with SQL Server Management Studio (SSMS) and Azure Data Studio (ADS).

If you only have SSMS, you'll need to have SQL Server Integration Services or SSDT installed to use its import and export options.

SSMS actually doesn't import and export directly; it calls the SQL Server Import/Export Wizard instead.

ADS, on the other hand, makes it easy to export data to Excel, JSON, CSV, and XML by default.

To import data in ADS, you'll need to install the SQL Server Import extension.

Azure Data Studio offers a useful extension for schema comparison, which you can install to compare database object schemas. This feature is a game-changer for developers who need to track changes.

You can compare schemas in Azure Data Studio, but not in SSMS, which lacks a schema compare option. This is a notable difference between the two tools.

To compare schemas in Azure Data Studio, you'll need to install the SQL Server Schema Compare extension. It's a straightforward process that will give you the ability to compare and contrast your database object schemas.

Spatial Viewer is a powerful tool for visualizing data.

You can use SSMS to visualize spatial data, which is not an option in ADS.

SSMS offers a Spatial Data Viewer, making it easier to understand complex data.

This feature is particularly useful for spatial data, allowing you to see patterns and relationships that might be difficult to discern in a table format.

SSMS 1, ADS 5 is the specific version where this feature becomes available.

Azure Data Studio (ADS) has some amazing features that set it apart from other tools like SQL Server Management Studio (SSMS). One of these features is the ability to connect to Hadoop.

You can also connect to PostgreSQL using an extension, which is a great option for developers who work with this database system. And if you're an Oracle user, you'll be happy to know that there's an extension available for that too.

Another feature that's worth mentioning is the Source Code Control, which allows you to manage your codebase more efficiently. This is especially useful for developers who work on large projects with multiple collaborators.

Here are some other ADS features that you might find useful:

These features make ADS a powerful tool for any data professional, whether you're working with SQL Server, Azure SQL Database, or other database systems.

Azure Data Studio offers a unified tooling experience for data professionals, focusing on the most commonly used functionality.

Built-in features like a query editor, native Jupyter Notebooks, and an integrated terminal provide a comprehensive environment for data operations.

Workspaces in Azure Data Studio are customizable, allowing you to personalize your environment to your most-used workflows.

With a platform that spans data operations, including management, deployment, and migration of Azure data services, you can streamline your processes.

You can add or remove functionality as needed, giving you access to only the features you require.

Azure Data Studio offers a multiplatform compatibility that sets it apart from other tools. It's based on Visual Studio, making it compatible with Windows, Linux, or Mac.

This means you can use it on your preferred operating system, without being limited to a specific one. I've seen colleagues who prefer working on Macs, and they can still use Azure Data Studio.

With Azure Data Studio, you can install it on your machine and start working on data operations, including management, deployment, and migration of Azure data services.

Many people, including me, like the dark theme.

SSMS can be dark, but it requires modifying the ssms.pkgundef file.

In ADF, the process is extremely simple.

Some users may not think the dark mode theme is important, but it can be a nice touch.

To enable dark mode in ADF, you don't need to go through a complicated process, unlike in SSMS.

The simplicity of enabling dark mode in ADF makes it a more user-friendly experience.

In environments where detailed control and extensive database management is required, SSMS really shines. It's uniquely tailored to handle complex database administration tasks in big environments, making it a great choice for huge databases.

SSMS is designed to handle complex database administration tasks in big environments, and its advanced capabilities are built to help you navigate and manage intricate database structures. This is particularly useful when dealing with intricate database structures.

If performance tuning is a big concern for you, SSMS is a great option. Its sophisticated tools provide granular insights into database performance, letting you fine-tune your database to optimize efficiency.

SSMS provides advanced data analysis and reporting features like SQL Server Analysis Services (SSAS) and SQL Server Reporting Services (SSRS), making it a good fit for complex data analysis or detailed report generation.

Here are some specific situations where SSMS might be a better choice than Data Studio:

SQL Management Studio (SSMS) is a software tool for configuring and managing Microsoft SQL Server, providing graphical tools and script editors for developers to interact with and manipulate SQL Server databases.

It's a closed-source but free application developed by Microsoft, allowing users and administrators to interact with SQL Server databases on-premises or in the cloud on Azure.

SSMS has been around since SQL Server 2005 and has been improving with new features, now up to version 20.1, but it's essentially the same Win32 application for Windows desktops.

It doesn't support MacOS or Linux, limiting its use to Windows-based servers or client stations.

SSMS provides a graphical interface for performing operations on SQL Server and its objects, as well as generating code for T-SQL, DMX, MDX, and DAX queries.

This makes it a powerful tool for database administrators and developers working with SQL Server.