Microsoft released SQL Server 2025 on November 19, 2024, during the Microsoft Ignite conference. With this release (currently in preview), SQL Server has now become an AI-ready database. Along with adding new AI capabilities - the need of the hour- Microsoft has integrated several of its services to enhance automation and performance. SQL Server 2025 also includes best-in-class security features, including enhanced credential management, improved compliance, and enhanced auditing capabilities. 

Let us discuss the important features of the new Enterprise AI-ready SQL Server 2025 database in detail.

Built-in AI 

With SQL Server 2025, the AI capabilities are now integrated into the database with Azure OpenAI and other AI services. So, there is no need for special code or logic to integrate various external services; everything can be handled in the database itself. Using the flexible AI model management in the SQL engine, you can bring AI models into the database workflow via REST APIs. This can be very useful across various domains, including healthcare, financial services, manufacturing, and retail, for efficiently processing large amounts of data and identifying accurate patterns.

The new release focuses on improving search results and simplifying RAG (retrieval augmented generation) using several tools and techniques.

With the introduction of the vector data type, Microsoft has taken SQL Server beyond traditional structured databases. Using this new vector data type, users can store data as vectors and perform AI-based vector search on the SQL data. 

Some examples of vector data can be images - stored as a set of vector values, large text - like a website page content, and other media.

How does storing data as vectors help?

Consider the simple example where, if you want to visit a website for the second time, you want it to remember the preferences you set when you visited for the first time. For example, you would want a specific news genre (let's say sports) on your news feed and are not interested in seeing any other news, like say cooking. Now, based on these preferences, the news app will recommend similar news items to you. If data is stored as vectors, it is more efficient for the database to search for items similar to your preferences and recommend them. 

You can also combine the vector and native indexes to perform hybrid data searches. SQL Server uses DiskANN for performing high-quality vector search, which uses the ANN (Approximate Nearest Neighbor) technique to find the closest match of a given input search string. 

Not only vector search, but you can also perform hybrid searches, i.e., text and images search combined (giving text and vector both as input), giving you answers that are semantically more appropriate. These results are not achievable with simple keyword search. SQL Server 2025 supports integration with Lang Chain, Semantic Kernel, and Entity Framework Core.

Another significant improvement in SQL Server 2025 is the enhancements to T-SQL. T-SQL, or Transact-SQL, is an extension of SQL that enables complex tasks. It includes several capabilities like control statements, stored procedures, built-in functions, etc. These features make it easy for programmers to perform tasks that would otherwise be complex. For example, T-SQL has a function named date_diff (), which helps you find the difference between two dates in SQL Server itself. This logic would have to be performed at the code level. Performing these operations at the database level is more performant. 

So, what enhancement to T-SQL makes it easier to work with AI models and services built into SQL Server itself?

Now, you can generate embeddings and text chunks directly using the T-SQL commands. You can call external REST endpoints directly from T-SQL stored procedures or functions using the sp_invoke_external_rest_endpoint command. Earlier, you had to leave the SQL environment and write code to integrate with external services. For example, if you want to get the stock prices of the day using a third-party service, you can simply invoke the API using this command, and you will get the response, all in the database itself.

You can then integrate the response into the SQL workflow without going back and forth between the business layer and database. 

SQL Server 2025 also introduces GraphQL integration through Data API Builder. This means the Data API builder can automatically generate a GraphQL schema with the query and required fields. For example, if you simply enable a database entity, say Customer as a GraphQL entity, the builder will generate the basic schema - the type of read queries, for example, get all customer details, get a single customer using ID field, and write queries, like create, update or delete customer based on id. This way, you can easily add, remove, or modify fields in your GraphQL queries without changing the backend implementation.

As you can see, the integration of AI within the SQL engine gives so many advantages to perform complex query operations, data analysis, and identifying patterns.

Enhanced security and performance

SQL Server 2025 comes with a lot of security and performance features, from enhanced data encryption to Role-based access control, data masking, auditing, compliance, and much more. 

SQL Server 2025 integrates with Microsoft Entra, the identity and access management solution, to enhance security. This ensures robust identity verification mechanisms, like multi-factor authentication, role-based access control, conditional access policies, and secured connections at all times. Microsoft Entra's Zero Trust principles are now integrated into SQL Server 2025, hence every access request is authenticated, authorized, and encrypted. 

Further, by using Managed Service Identity (MSI), SQL Server can securely authenticate outbound connections without requiring hard-coded credentials, thereby reducing credential exposure. This is particularly useful when you want to perform an outbound operation from your SQL Server instance, like calling a third-party API, without exposing your credentials. All this is very simple to set up. You can enable Azure Arc for your SQL Server instance, configure MSI through the Azure portal, and perform the required outbound operation.

To improve performance, Microsoft has introduced enhanced query optimization and execution. SQL Server can choose the optimal execution plan based on customer-provided runtime parameter values using the Optional Parameter Plan Optimization (OPPO). In most cases, a single (cached) execution plan may not be the most optimal (due to bad parameter sniffing). OPPO aims to solve this issue by dynamically selecting the best plan for a given set of parameter values. This improves the performance and leads to more efficient usage of database resources.  

A few other significant performance improvements in SQL Server 2025 are:

• Persisted statistics on secondary replicas - this prevents loss of statistics due to restart or failure. 
• Improvements in batch mode processing - this means multiple rows can be processed at the same time, leading to faster query execution and reduced CPU usage. 
• Improvements to columnstore indexing - better compression and faster query execution make it easier to perform complex data analytics and handle large volumes of data for processing, making SQL Server 2025 a mission-critical database.
• Concurrent transactions - SQL Server 2025 introduces Transaction ID (TID) and Lock After Qualification (LAQ) to minimize blocking for concurrent transactions. Using TID, SQL Server can manage locks more efficiently, reducing lock contention and speeding transaction processing. Similarly, locks are acquired only when required, thereby reducing blocking or delaying other transactions and improving overall performance. 

SQL Server 2025 also introduces a native capability for real-time change event streaming. This enables the database to capture and publish data and schema changes in near real-time to event streaming platforms like Azure Event Hubs and Kafka. By capturing and streaming changes as they happen, SQL Server 2025 enables real-time analytics and decision-making, providing immediate insights and actions. This could be useful in scenarios such as automatically and immediately updating inventory when a purchase is made, or updating dashboards in real time to provide sales insights for the day or hour. 

SQL Server 2025 also supports implementing CQRS (Command Query Responsibility Segregation) patterns, enabling better separation of read and write operations and improving performance and scalability.

Integration with Microsoft Azure Arc and Fabric

Whether your SQL server instance is on-premises, in the cloud, or elsewhere, by integrating it with Azure Arc, you can manage it from a single place. You can also run your instances in a hybrid environment, for example, by connecting your on-premise database with cloud services! Azure Arc also handles security, compliance, and resource optimization. 

Let's take a simple example of a retail chain to illustrate this. Let's say this chain has around 10 stores across different locations, each with a local SQL server instance, inventory management, and customer data. For analytics and reporting, you also have cloud services. Now, managing all 10 stores could pose challenges - unless you have  Azure Arc, a centralized, unified platform to manage all 10 stores centrally. You can apply consistent security policies and updates, perform centralized data analytics, enable real-time data integration, and optimize resources.

Microsoft Fabric is a unified data platform that brings a suite of services, including Data Engineering, Data Factory, Data Science, Real-Time Analytics, Data Warehouse, and Databases, together. Fabric eliminates the need for extensive ETL processes and enables near real-time analytics. With SQL Server integration, you can build AI-powered applications directly within your SQL Server instance. 

For example, you want to analyze customer purchase trends for a particular time of day. Data is captured in SQL Server 2025, and Microsoft Fabric can process real-time data streams, integrate with AI-powered models to provide the required analytics, and generate reports and dashboards instantly.

Summary

In this blog, we have touched upon the important features introduced in SQL Server 2025, with a strong focus on its AI-readiness. All these features look highly promising and could revolutionize database management. Integrating Azure services with SQL Server will enhance the database's capabilities more than ever, enabling seamless end-to-end workflows, boosting developer productivity, and improving overall application performance.