With the continuous advancement of the world of data management, Microsoft SQL Server 2025 It has emerged as a revolutionary release that offers a set of new features and improvements to meet the needs of modern organizations. This article explores the new capabilities SQL Server 2025 It shows how this database is ready for enterprise AI processing from the ground up to the cloud.

Integrating AI and vector database capabilities

One of the most exciting developments SQL Server 2025, its deep integration with Artificial Intelligence (AI) This version includes built-in features Artificial intelligence is to develop programs AI and patterns Recovery Augmented by Production (RAG) Makes it easier. With vector support Safe, fast and easy, developers can Combine vectors with SQL data To perform a hybrid vector search based on artificial intelligence.

SQL Server 2025 It has evolved into a standalone vector database that leverages the capabilities of Internal filtering Along with Vector search This feature is achieved by using DiskANN, a vector search technology based on Disk storage spaceIt works and allows for finding similar data points in very large data sets with high efficiency.

Vector search technology

Vector search technology in SQL Server 2025 It is a major breakthrough for applications that require processing high-dimensional data. Here are some of its key aspects:

• Native support for vectors: SQL Server 2025 Introduces native vector data types and vector indexes that allow developers to perform efficient searches and analysis on large volumes of vector data.
• DiskANN: Vector search by DiskANN Supported, a technology that uses disk storage to efficiently find similar data points in large data sets. DiskANN Search abbreviation Disk-based approximate nearest neighbor It is designed to process high-dimensional data and provides fast and accurate search results.
• AI Hybrid Search with Vectors: By combining vectors with SQL data, SQL Server 2025 Enables AI hybrid search with vectors. This means developers can use Traditional SQL queries and vector search capabilities in the same database, which is a powerful tool for applications Artificial intelligence Provides.
• Internal filtering: Built-in filtering capabilities make searches more precise and efficient, making it easier to find relevant data points in large data sets.

Improved performance and security

Performance and security always at the core SQL Server They were located and the version 2025 It continues this tradition with several improvements. The new version includes **optimized locking, optional parameter program optimization, faster batch mode, and improved indexing. columnstore In addition, this version includes Automated credential management and reduce potential vulnerabilities with Microsoft Entra Managed Identities It is.

Integration with Microsoft Fabric and Azure

SQL Server 2025 Integrated with Microsoft Fabric and Azure It is integrated to provide seamless near-real-time analysis through Fabric database mirroring This integration enables cloud security, management, and agility anywhere through Azure Arc This release also supports hybrid environments across clouds, on-premises data centers, and the edge, and includes innovations Microsoft Azure It is used for customer databases.

New T-SQL functions and JSON support

Developers of new functions T-SQL Introduced in SQL Server 2025 will welcome, including support for Regular expressions Regular Expressions and new functions JSON T-SQLThis version also includes the data type JSON and JSON index The ability to work with data is JSON directly inside SQL Server It improves.

GraphQL and REST API support

SQL Server 2025 Support for GraphQL through Data API Builder (DAB) introduces, which allows developers to Flexible and efficient APIs Build. GraphQL A query language for APIs that allows clients to request exactly the data they need, making it easier to build powerful and efficient applications. With GraphQLDevelopers can define the structure of the responses they want to receive, which reduces the amount of data transmitted over the network and improves performance.

In addition, this engine is now REST API Through sp_invoke_external_rest_endpoint supports, which allows for seamless integration with external services. This feature allows SQL Server This allows you to interact with web services directly from within the database. RESTful interact, making it easier to integrate with various external systems and services. Developers can use this capability to Data extraction From External APIs, sending data to other services and perform other tasks without leaving the environment SQL Server Use.

Managing AI models and low-code tools

SQL Server 2025 Flexible management of models Artificial intelligence through interfaces Representational State Transfer (REST) Inside the engine SQL Server This introduces the possibility of using artificial intelligence models from Beginning to the Cloud and provides a unified experience for managing AI workloads. Tools Low coding Flexibility model interfaces in the engine SQL They offer that by T-SQL and External REST APIs These tools enable developers to create diverse AI applications through seamless integration with popular AI frameworks such as LangChain, Semantic Kernel and Entity Framework Core They strengthen.

AI model management capabilities include:

• Deploying models: Easily create AI models through REST APIs In the environment SQL Server Deploy. This simplifies the process of integrating AI models into your database workflows.
• Model Management: Models that through T-SQL are available through REST APIs Manage and secure so your AI models are always up-to-date and secure.
• Low-code tools: Use low-code tools to build and manage AI models, which reduces the complexity of AI development and enables faster deployment.

Real-world use cases

Advanced features SQL Server 2025 It has been applied in various real-world scenarios, demonstrating its power and flexibility:

• Retail industry: Sellers from SQL Server 2025 For inventory management and customer behavior analysis in Real time Hybrid vector search capabilities help them identify trends faster and optimize inventory levels.
• Health and Treatment Department: Health care providers from Artificial Intelligence Integration and technology Vector search They are used to analyze patient data, predict health outcomes, and personalize treatment plans. Built-in filtering capabilities ensure accurate and efficient data searching.
• Financial Services: Financial institutions from SQL Server 2025 To identify Fraud and risk management. Improved performance and security features help them process large volumes of transactions securely and efficiently.
• Manufacturing industry: Producers of Managing AI models and Low-code tools SQL Server 2025 They use it to optimize production processes and predict equipment failures. Integration with Microsoft Fabric and Azure Enables data analysis and integrated decision-making.

Performance criteria

SQL Server 2025 It has shown significant performance improvements over its previous versions. Here are some key metrics:

• Faster query execution: SQL Server 2025 Relative to SQL Server 2022 For workloads Analytical, Machine Learning Inference and Loading data It is faster. The new version of the database performance in Memory And it improves scalability and reduces query execution time.
• Optimized query processing: Improved optimization and query execution capabilities ensure that Complex queries They are processed more efficiently and have faster response times.
• High throughput: SQL Server 2025 Several top performance metrics for transaction processing with Leading business plans This includes criteria such as: HammerDB TPROC-C and TPROC-H It measures the database's ability to process high volumes of transactions.
• Scalability: The new version supports larger data sets and higher concurrency levels, making it ideal for Enterprise-scale applications Makes it suitable.

Conclusion