SQL Server 2025: New Features and Enhancements

SQL Server 2025 is Microsoft’s next-generation database platform that integrates AI, real-time analytics, and advanced security directly into the engine. It automates query optimization, resource management, and performance tuning, making databases smarter and more efficient.

In this SQL Server tutorial, you will explore SQL Server 2025, its key features, including vector data support, JSON indexing, event streaming, and developer tools like REST API and fuzzy matching. These enhance efficiency, security, and modern database management. SQL Server skills can boost your earning potential by 22% in the next 3 years. Enroll in our Free SQL Server Training Online with Certificate today.

What is SQL Server 2025 ?

SQL Server 2025 is Microsoft’s next-generation relational database platform designed to support modern data-driven enterprises. It goes beyond traditional data storage by combining artificial intelligence, automation, cloud integration, and real-time analytics into a single powerful system. This version focuses on making databases smarter, faster, and more secure while reducing manual administration.

• It is an intelligent database platform that uses AI to optimize queries.
• It is fast and responsive thanks to real-time analytics and event streaming.
• It is secure and compliant with Microsoft Entra authentication and TLS 1.3.
• It is developer-friendly with REST API support, regex, and fuzzy matching.
• It is self-optimizing and efficient using AI-driven tuning and predictive monitoring.

TOP 12 NEW FEATURES IN SQL SERVER 2025

1. Built-in AI: Vector Data Types and Search

Key Features:

• Native vector datatype for AI embedding storage
• Similarity search using cosine and distance algorithms
• Faster semantic query execution within database engine
• Supports recommendation and AI-powered search systems
• Eliminates need for external vector databases

Example:

SELECT * FROM products
ORDER BY VECTOR_DISTANCE(embedding, @query_vector)

2. Native JSON Support with Indexing

Key Features:

• Faster querying of stored JSON documents
• Index support on JSON object properties
• Simplified ingestion of semi-structured application data
• Improved performance for API-driven database workloads
• Easier schema evolution without table redesign

Example:

CREATE INDEX idx_json ON users(data.jsonValue('$.email'))

3. Regular Expressions in T-SQL

Key Features:

• Pattern-based search using SQL regular expressions
• Built-in regex validation within SQL statements
• Simplifies advanced text filtering operations
• Improves cleansing of large textual datasets
• Eliminates dependency on application-level regex

Example:

SELECT * FROM users 
WHERE email REGEXP '^[a-z0-9]+@gmail.com$'

4. Change Event Streaming

Key Features:

• Streams insert, update, and delete activity instantly
• Enables real-time analytics pipelines and dashboards
• Integrates with Kafka, Azure, and streaming tools
• Improves consistency between transactional and analytical systems
• Reduces lag in business intelligence reporting

Example:

CREATE EVENT STREAM orders_stream TO 'AzureEventHub'

5. Fabric Mirroring for Real-Time Analytics

Key Features:

• Continuous syncing between SQL and Fabric analytics
• Eliminates traditional ETL delays and pipelines
• Enables near real-time business intelligence dashboards
• Maintains consistency without performance impact on source
• Simplifies hybrid analytics architecture significantly

Example:

ENABLE FABRIC_MIRRORING ON DATABASE salesdb

6. Enhanced Security: Microsoft Entra and TLS 1.3

Key Features:

• Centralized identity enforcement through Microsoft Entra authentication
• Mandatory secure encrypted connections using TLS 1.3
• Improved access control for applications
• Reduced handshake time and connection attacks
• Compliance with enterprise-grade security regulations

Example:

CREATE LOGIN FROM EXTERNAL PROVIDER

7. Performance Boosts: OPPO and Optimized Locking

Key Features:

• Faster query compilation and execution planning
• Reduced query optimization overhead significantly
• Improved concurrency for high transaction systems
• Intelligent lock escalation avoidance mechanisms
• Faster response under heavy database workloads

8. Developer Tools: REST Invocation and Fuzzy Matching

Key Features:

• REST API calls directly from SQL agent
• Enables automation with external cloud services
• Built-in fuzzy logic for approximate text matching
• Simplifies third-party API integration workflows
• Improves data cleansing and deduplication

Example:

SELECT * FROM REST_CALL('https://api.service.com/data')

9. Availability Enhancements

Key Features:

• Intelligent failover based on workload behavior
• Reduced planned and unplanned downtime
• Faster recovery during node failures
• Improved Always-On cluster performance
• Zero-touch maintenance upgrades supported

10. Columnstore and TempDB Improvements

Key Features:

• Faster compression and decompression algorithms
• Improved read speed for analytical workloads
• Reduced TempDB contention under load
• Better memory utilization for columnstore operations
• Improved divide-and-conquer batch execution

11. PolyBase Expansions

Key Features:

Example:

SELECT * FROM OPENROWSET(BULK 's3://bucket/file.csv')

12. Query Store on Secondaries

Key Features:

• Monitors query performance on secondary replicas
• Detects regressions in standby systems
• Improves read-only workload optimization
• Enables query tuning on replicated nodes
• Enhances stability of reporting servers

SQL Server 2022 vs SQL Server 2025

Microsoft SQL Server 2025 is a major evolution over SQL Server 2022, focusing on AI integration, automation, real-time analytics, and cloud-first design. While SQL Server 2022 introduced hybrid cloud support, SQL Server 2025 expands this with built-in intelligence, better developer experience, and real-time data streaming.

AI Integrated into the SQL Server 2025 Database Engine

1. Self-Optimizing Query Execution: The database automatically improves execution plans using machine learning based on workload patterns.
2. Automatic Index Management: Indexes are created, tuned, or removed intelligently without requiring constant DBA involvement.
3. Predictive Performance Monitoring: AI identifies slowdowns and risks before they affect production systems.
4. Adaptive Resource Allocation: CPU, memory, and I/O usage are balanced dynamically based on real-time demand.
5. Autonomous Diagnostics and Healing: Errors and performance issues are detected and corrected automatically.

How to Upgrade to SQL Server 2025?

Step 1: Check Compatibility

Step 2: Take Full Backup

Step 3: Fix Reported Issues

Step 4: Install SQL Server 2025

Step 5: Upgrade Compatibility Level

Step 6: Test and Monitor

Conclusion

Take our Sqlserver skill challenge to evaluate yourself!

In less than 5 minutes, with our skill challenge, you can identify your knowledge gaps and strengths in a given skill.

GET FREE CHALLENGE