GitHub Copilot arrives in SSMS 22: AI to accelerate SQL development

Artificial intelligence continues to redefine software development and database management. A clear example is the arrival of GitHub Copilot in SSMS 22. Since October 14, GitHub Copilot has been available in preview mode within SQL Server Management Studio 22, offering direct integration in the query editor. Thanks to this innovation, SQL developers now have access to an intelligent assistant capable of generating queries, optimizing code, and explaining scripts in natural language. In short, it’s a more powerful and efficient solution that helps reduce repetitive tasks and create solutions for SQL Server and Azure SQL Database environments, among others.

How does it work? Here’s a quick overview:

1. GitHub Copilot in SSMS requires a GitHub account with Copilot access.
2. From SSMS, you can choose the AI model you want to use to generate responses.
3. Your message is then sent to the selected model.
4. The model processes your input and generates the appropriate response.
5. The response appears in the SSMS editor, ready to be used in your code.
6. Copilot can include contextual data such as the SQL Server version you’re connected to, information about your database, and more.

What’s new with this integration?

Developers now have an intelligent assistant built into SSMS, eliminating the need for external tools.

• Copilot can create complex queries, stored procedures, and maintenance scripts.
• It doesn’t just generate code—it also improves existing scripts for optimized performance and fewer errors.
• Responses vary depending on the SQL Server version and the connected database.
• Works with both on-premises SQL Server and Azure SQL Database.
• Copilot frees up time so teams can focus on more advanced tasks, from backups to index creation and user management.

Personalizing the assistant: When to use GPT-4 vs. GPT-4 Turbo?

Another key feature of this integration is the ability to select the AI model that best fits your project. This can positively impact response speed, suggestion depth, and operational costs.

GitHub Copilot offers two main options in SSMS: GPT-4 and GPT-4 Turbo. Here’s what each brings:

1. GPT-4 is designed for maximum precision in code creation. It’s ideal for complex queries, advanced optimization, and detailed script explanations. However, response times are longer. A typical GPT-4 use case would be SQL code audits and query optimization for complex analytical workloads.
2. GPT-4 Turbo is optimized for repetitive tasks, fast script generation, and bulk operations. It reduces resource consumption and speeds up delivery times. GPT-4 Turbo is perfect for producing maintenance scripts and generating reporting queries quickly.

In short, critical projects benefit from GPT-4’s quality, while routine tasks are best handled by GPT-4 Turbo.

Looking ahead: Future improvements for SSMS and Copilot

Microsoft has announced plans to continue evolving SSMS, aiming to make it a comprehensive tool for SQL database administration across the Microsoft ecosystem.

Key areas of focus include:

• Expanded compatibility with SQL Server 2025 (17.x).
• Enhanced integration with Fabric SQL.
• Optimized support for Arm64 architectures.
• User experience improvements such as new customization options, advanced grid export, and a more powerful object explorer.
• New AI-based tools to boost productivity, including query editor auto-complete, agent mode for complex tasks, and the ability to export chat conversations.

The integration of AI into tools like SSMS is redefining how we develop software, delivering greater efficiency, quality, and scalability to projects. At Itequia, we work to help companies like yours strategically incorporate AI into their solutions—optimizing processes and accelerating innovation. Our approach focuses on building custom applications that leverage AI’s potential to deliver tangible, sustainable results. Discover how to integrate AI into your SQL environment with our help. Contact us today.