SQL Server Management Studio (SSMS) 21 is now generally available (GA)
The SQL Tools team is thrilled to announce the general availability of SQL Server Management Studio (SSMS) 21. SSMS 21 GA brings a modern installation and update experience through the Visual Studio installer, 64-bit support, Git integration, and initial dark theme support.SQL Server 2025 is Now Generally Available
Today at Ignite, we announce the general availability of SQL Server 2025. This marks the latest milestone in the more than 30-year history of SQL Server. It is also a key part of our commitment to the one consistent SQL promise, delivering consistent experience across on-premises, cloud, and SaaS environments, with one engine and one unified platform. Built on SQL Server’s foundation of best-in-class security, performance and availability, SQL Server 2025 is the AI-ready enterprise database and it redefines what's possible for enterprise data. With built-in AI and developer-first enhancements, SQL Server 2025 empowers customers to accelerate AI innovation using the data they already have, securely and at scale, all within SQL Server using the familiar T-SQL language. SQL Server 2025 is designed to meet customers where they are, whether on-premises, in the cloud, or in hybrid environments, helping you build intelligent, secure, scalable, and consistent solutions that drive real business outcomes. SQL Server 2025 is experiencing significant momentum, as evidenced by 10,000 organizations participating in the public preview and 100,000 active SQL Server 2025 databases. Leading customers like Mediterranean Shipping Company (MSC), Infios, and Buhler are already advancing with SQL Server 2025, supported by a robust ecosystem of technology partners including AMD, Canonical, HPE, Lenovo, NVIDIA, Pure Storage and Red Hat. Key Innovations in SQL Server 2025 AI built-in AI is now integrated directly into the SQL Server engine, enabling advanced semantic search for deeper insights and natural language experiences across enterprise data. Model management is built into T-SQL, supporting seamless integration with Microsoft Foundry, Azure OpenAI Service, OpenAI, Ollama, and more—deployable securely anywhere, from on premises to the cloud. Developers can easily switch between models without changing code, and essential AI building blocks like vector embedding, text chunking, and DiskANN indexing are natively supported. Integration with frameworks such as LangChain and Semantic Kernel accelerates AI-powered app development. At Ivanti, our mission is to elevate human potential by managing, protecting, and automating technology to drive continuous innovation. SQL Server 2025 plays a crucial role in helping us achieve this goal. By harnessing the advanced capabilities of SQL Server 2025 and Azure OpenAI, we are building intelligent, agentic tools that empower customers to access knowledge and resolve incidents faster. Sirjad Parakkat, Vice President, AI Engineering | Ivanti Made for developers This release is the most significant for SQL developers in a decade, streamlining development and boosting productivity. Native JSON support, REST APIs,RegEx and Fuzzy string match enable richer data enrichment and validation. Change event streaming allows real-time, event-driven applications by streaming changes directly from transaction to Azure Event Hubs, reducing resource overhead compared to CDC. SQL Tooling SQL Server 2025 delivers major updates across the data platform. SQL Server Management Studio (SSMS 22) is now generally available, offering official support for SQL Server 2025, enhanced AI assistance, and ARM64 support. SSMS 22 also includes AI assistance when you install the GitHub Copilot workload, which leverages the same GitHub subscription you use with GitHub Copilot in Visual Studio or VS Code. The Microsoft Python Driver for SQL Server (mssql-python) is generally available, providing a modern, high-performance connector with Entra ID authentication. "SQL Server 2025 offers two major functionalities which are very important to us and will bring SQL Server into the future – native API calls and RAG. In the past we’ve had to use custom assemblies for making API calls, which can be a huge problem when you have to make hundreds of thousands of API calls and the remote systems are slow to respond, creating large queues and high CPU load in SQL. With RAG and vector search, we can now implement countless AI possibilities, making data searchable in ways previously impossible.” Alex Ivanov, CTO, eDynamix Best-in-class security, performance, and availability SQL Server 2025 builds on its foundation as the most secure database in the last decade, introducing modern identity and encryption practices, including Microsoft Entra managed identities for improved credential management. Optimized locking reduces lock memory consumption, minimizes blocking, and boosts concurrency. Tempdb space resource governance improves server reliability. Optional parameter plan optimization makes query performance more stable. SQL Server 2025 continues to strengthen its mission-critical capabilities with enhancements to Always On availability groups (AGs) and disaster recovery options. The focus is on faster failover, improved diagnostics, and hybrid flexibility. Preliminary benchmarks show SQL Server 2025 running on AMD EPYC processors with HPE hardware delivers measurable gains in performance and value. For performance, the 10TB workload sets a new record for SQL Server. In price-performance, SQL Server 2025 achieves a 4% improvement in the 3TB category compared to previous results. “At Infios, we are very excited about several new features in SQL Server 2025 and the vast amount of opportunities for performance improvements. We are most excited about the optimized locking feature and how that can drastically help reduce locking across our customers and all their unique workloads. Optional Parameter Plan Optimization (OPPO) could also be huge for us with SQL Server being able to reduce parameter sniffing issues. Persisted statistics on secondary replicas will also be beneficial for the rare occurrence that we have a failover event. While we’ve been pleased with all the improvements to tempdb in previous versions, resource governance to prevent runaway queries and consuming large amounts of disk space in SQL 2025 is a big improvement for us. ” Tim Radney, SaaS Operations Manager, Infios Cloud agility through Azure and Fabric SQL Server 2025 enhances cloud agility with support for database mirroring in Fabric, enabling near real-time analytics with zero-ETL and offloading analytical workloads. Azure Arc integration continues to provide unified management, security, and governance for SQL estates across on-premises and cloud environments, empowering organizations to scale and modernize with confidence. “With Fabric Mirroring in SQL Server 2025, ExponentHR can effortlessly mirror numerous datasets to fabric, enabling near real-time analytics. This technology has alleviated the need for expensive and complex ETL operations and enables more productivity for our customers. Thanks to SQL Server 2025’s built-in cloud connectivity, we can directly process large amounts of data efficiently and overcome traditional bottlenecks.” -- Brent Carlson, IT Manager, ExponentHR SQL Server 2025 on Linux SQL Server 2025 on Linux introduces several important enhancements. Security is strengthened with TLS 1.3 support, custom password policies, and signed container images. Platform support expands to include RHEL 10 and Ubuntu 24.04, while performance is improved through tmpfs support for tempdb and container-based deployments. Advanced analytics are enabled with generic ODBC data source support via PolyBase. Developer experience is streamlined with Visual Studio Code integration for local container deployment using the mssql extension and validated deployment patterns in partnership with Red Hat, supporting modern workloads and AI scenarios across hybrid environments. "The work we’re doing with Microsoft to optimize SQL Server on Red Hat Enterprise Linux is a powerful testament to the strength of our collaboration. With the new features in SQL Server, including support for Red Hat Enterprise Linux 10 and enabling streamlined deployment via Red Hat Ansible Automation Platform, we are making it easier than ever for customers to deploy and manage this critical workload across the hybrid cloud. This collaboration extends beyond just enabling core performance to deliver innovative, validated patterns, such as leveraging Red Hat Enterprise Linux AI with SQL Server for retrieval-augmented generation (RAG) and generative AI scenarios, and providing a more consistent experience for customers, whether they are deploying via the Azure Marketplace or on-premises. Our mutual goal is to minimize complexity, increase confidence and help enterprises harness the full potential of their data and AI investments on a trusted, open foundation." - Gunner Hellekson, Vice President and General Manager, Red Hat Enterprise Linux, Red Hat SQL Server 2025 on Azure Virtual Machines Run SQL Server 2025—any edition, Standard, Enterprise, Enterprise Developer, or the new Standard Developer Edition—on Azure Virtual Machines, using optimized VM families like Mbdsv3, Ebdsv5/6, and FXmdsv2 for high performance. Pair with Premium SSD v2 or Ultra Disk storage to achieve fast throughput, low latency, and excellent scalability. Deploy quickly from the Azure portal with features including configurable settings, flexible licensing, storage setup for data, logs, and tempdb, automated patching, and Best Practice Assessment (BPA). Get started today to leverage SQL Server 2025 and Azure’s high performance and flexibility. Preview Features & Flexibility In SQL Server 2025, customers can explore new database features using an opt-in mechanism through database-scoped configurations. Certain features, such as vector indexes, are introduced this way, allowing customers to try them in preview even while SQL Server is generally available. These features will become fully available in a future SQL Server 2025 update, at which point the database-scoped configuration will no longer be required. Our goal is to make preview features generally available within approximately 12 months, guided by customer feedback and our commitment to delivering high-quality experiences. Learn more. Product Changes SQL Server 2025 brings important changes to the product lineup. Standard edition changes: Resource limits have increased to support up to 32 cores and 256 GB of memory. Resource governor is now available in Standard edition. The newly launched Standard Developer edition offers full feature parity with the Standard edition, enabling development and testing that mirrors production environment capabilities. Power BI Report Server entitlement is now included for all editions except the Express edition, adding value for customers. Express edition changes: The maximum database size is now increased to 50 GB per database. The Express Advanced mode has been consolidated into a single, unified SQL Express edition, featuring all feature capabilities that were available in Express Advanced. Discontinuing Web edition in SQL Server 2025 release: SQL Server 2022 is the final version of the Web edition, with SQL Server 2022 Web edition remaining supported until January 2033 in line with Microsoft’s fixed lifecycle policy. If you've been using the Web edition for cost-effective web applications, now is a great time to consider migrating to Azure SQL. Azure SQL offers an affordable, scalable solution that is well-suited for modern web workloads. For multi-tenant apps, Azure SQL Database elastic pools provide flexible pricing and easy management—making the move to Azure SQL a smart choice for future growth. If you remain on-premises or use Azure SQL Virtual Machines, upgrade to the Standard edition. Modern Reporting and Analytics On-premises SQL Server Reporting Service (SSRS) consolidated into Power BI Report Server is now the default reporting solution, unifying paginated and interactive reports for all paid SQL Server licenses. Learn more. SQL Server Analysis Services 2025 introduces major performance enhancements, including improved MDX query efficiency, parallel DirectQuery execution, and visual DAX calculations for simplified modeling. It also adds new DAX functions, client library updates, and deprecates PowerPivot for SharePoint, while discontinuing HTTP access via msmdpump.dll by default. Learn more. SQL Server Integration Services (SSIS) now introduces support for the Microsoft SqlClient Data Provider in ADO.NET connection manager, enhancing connectivity and modernizing data integration workflows. Learn more. Partner Momentum Partners such as AMD, Intel, and HPE are collaborating on advanced performance and high availability solutions, including benchmark testing on AMD EPYC and Intel Xeon processors, with HPE achieving world record results for performance and price/performance. NVIDIA is working with SQL Server 2025 to enable streamlined deployment of GPU-optimized AI models using built-in REST APIs, supporting flexible AI workloads across environments. Pure Storage is delivering high availability and fast backup solutions through deep integration with SQL Server 2025, including metadata-aware snapshots and automation for simplified operations. Additionally, Microsoft works closely with partners like Canonical and Red Hat to ensure SQL Server is integrated seamlessly and operates effectively within the Linux ecosystem, providing customers with robust and reliable database solutions across a broader range of environments. Get Started Today SQL Server 2025 reaffirms Microsoft’s commitment to innovation, performance, and developer empowerment. We thank our customers, partners, and community for your ongoing support and feedback. We look forward to seeing what you build next with the AI-ready enterprise database. Download SQL Server 2025 today One consistent SQL: the launchpad from legacy to innovation Learn more through documentation and our Mechanics video Master SQL Server 2025 with a full learning path and claim your badge Get started with Azure SQL Share your feedback at SQL CommunitySQL Server 2025 - AI ready enterprise database from ground to cloud
The new version of SQL Server is designed to be an AI-ready enterprise database platform, integrating seamlessly from ground to cloud to Fabric. In this blog, we will explore the key features and enhancements that make SQL Server 2025 a game-changer for developers, database administrators, and organizations. The new capabilities build upon more than three decades of SQL Server innovation in performance, availability, reliability, and security, adding a host of new features that empower developers, protect data, and enable seamless analytics through the Microsoft Fabric integration. AI integration SQL Server 2025 offers features to support enterprise applications. This version integrates AI with customer data using AI capabilities within the SQL engine, ensuring that AI models remain isolated securely. The built-in vector data type allows hybrid AI vector searches, combining vectors with SQL data for efficient and accurate data retrieval. This integration facilitates AI application development and retrieval-augmented generation (RAG) patterns, and AI Agents using the familiar T-SQL syntax. The new vector data type stores vector embeddings alongside relational data, enabling semantically related searches within SQL Server. New vector functions perform operations on vectors in binary format, enabling applications to store and manipulate vectors directly within the SQL database engine. SQL Server 2025 includes T-SQL functions that provide the necessary tools for working with embeddings, without requiring detailed knowledge of their usage. Vectors enable AI models to identify similar data using the K-Nearest Neighbors (KNN) algorithm, with metrics like dot product or cosine similarity. To enhance scalability, SQL Server 2025 incorporates Approximate Vector Index and Vector Search, leveraging Approximate Nearest Neighbors (ANN) for faster, resource-efficient, and accurate results. SQL Server 2025 introduces advanced AI model management capabilities designed to enhance the efficiency and security of interacting with Azure OpenAI and other AI models. SQL Server 2025 provides options for deploying AI models either on-premises or in the cloud, with compatibility for Azure OpenAI, OpenAI endpoints, and Ollama. With all these capabilities, SQL Server 2025's hybrid search represents a paradigm shift in how organizations access and utilize data. Through a blend of keyword and vector searches, businesses can unlock deeper insights, improve customer satisfaction, and harness the full potential of their data assets. Our customer, Kramer & Crew GmbH & Co, who participated in our Early Adoption Program (EAP) aka private preview shared us below. "Joining the EAP was a great opportunity to explore the new AI, security, performance, Fabric, and Azure Arc features! With the new semantic search and RAG capabilities in SQL Server 2025, we can empower existing GenAI solutions with data embeddings to create next-generation, more intelligent AI applications. By connecting systems (e.g., ITSM, CRM, ERP, and others), we deliver a seamless, natural conversational experience across enterprise environments." Markus Angenendt, Data Platform Infrastructure Lead, Kramer & Crew GmbH & Co. KG Developer productivity SQL Server 2025 introduces several exciting developer features designed to enhance developer productivity. New GitHub Copilot: GitHub Copilot transforms coding with AI-driven suggestions, streamlining workflows and enhancing efficiency. Its agent mode proposes edits, tests, and validates changes, enabling developers to focus on complex tasks. SQL Server Management Studio (SSMS) 21: Releasing SQL Server Management Studio (SSMS) 21, for general availability (GA). SSMS 21 includes support for SQL Server 2025. The Copilot in SSMS – now available in preview. New Python Driver: The Python driver for SQL Server and Azure SQL offers efficient, asynchronous connectivity across platforms like Windows, Linux, and macOS. It's designed to simplify development and enhance performance for data-driven applications. Standard Developer Edition: SQL Server 2025 Standard Developer Edition is a free edition licensed for development and test purposes. The intent is to enable all features of SQL Server Standard Edition to facilitate the development and testing of new applications that use the Standard Edition in production. This edition complements the existing Enterprise Developer Edition. JSON data type and aggregates: SQL Server 2025 includes a native JSON data type, allowing for more efficient storage and manipulation of JSON data up to 2GB storage per JSON document. This type supports various JSON aggregate functions to facilitate the aggregation of JSON data. Queries over JSON documents can be optimized by creating a JSON index and using JSON functions and methods to modify and search data natively. Regular expressions (RegEx): SQL Server 2025 introduces support for Regular Expressions (RegEx), providing powerful tools for developers to efficiently query and manipulate text data, better matching pattern than “LIKE” operator. External REST endpoint invocation: The sp_invoke_external_rest_endpoint stored procedure allows for the native invocation of any REST endpoints directly from within T-SQL, enabling seamless integration with external web services. Change event streaming (CES): Enables real-time data integration by streaming data changes directly from SQL Server to Azure Event Hubs with Kafka compatibility, facilitating near real-time analytics and event-driven architecture based on Transaction log. Consider using Change Event Streaming for CDC as it eliminates the need for I/O operations, offering a more efficient and streamlined solution for developers. New T-SQL functions: Several new T-SQL functions introduced to simplify complex queries and increase workload performance. For example, the PRODUCT() aggregate function calculates the product of a set of values. New Chinese collations: Support for GB18030-2022 collation standard. Overall, these developer-centric enhancements in SQL Server 2025 streamline the process of building modern, AI powered and data-rich applications. They reduce the need for custom code and encourage a more declarative, in-database approach to data processing, which can lead to simpler architecture and better performance. “The introduction of the new PRODUCT() aggregate function in SQL Server 2025 has streamlined this process, reducing code complexity while improving computational efficiency by over 30%. This enhancement accelerates key economic calculations, including the computation of the U.S. Gross Domestic Product (GDP), and also strengthens organizations’ ability to deliver timely, accurate data to policymakers and to the public." -- David Rozenshtein and Sandip Mehta, IT Modernization Architects, Omnicom Consulting Group” Secure by default SQL Server 2025 delivers a range of advanced security features designed to enhance data protection, authentication, and encryption. Here are the key security enhancements. Stop using client secrets and passwords: SQL Server 2025 supports managed identity authentication enabled by Azure Arc. This feature allows secure authentication for outbound connections to Azure resources and inbound connections for external users. For example, backup to Azure Blob Storage can now use SQL Server managed identity for authentication. Stronger encryption: To protect the key material of a symmetric key SQL Server stores the key material in encrypted form. Historically, this encryption utilized PKCS#1 v1.5 padding mode; Optimized starting with SQL Server 2025, the encryption uses Optimal Asymmetric Encryption Padding (OAEP) for encryption by certificate or asymmetric key. Stronger password encryption: To store a SQL user password we use an iterated hash algorithm, RFC2898, also known as a password-based key derivation function (PBKDF). This algorithm uses SHA-512 hash but hashes the password multiple times (100,000 iterations), significantly slowing down brute-force attacks. This change enhances password protection in response to evolving security threats and helps customers comply with NIST SP 800-63b guidelines. Strict connection encryption: The implementation of Extended TDS 8.0 support and TLS 1.3 for stringent encryption protocols enhances the security of internal component communications within SQL Server 2025. Optimized security cache: When security cache entries are invalidated, only those entries belonging to the impacted login are affected. This minimizes the impact on non-cache permissions validation for unaffected login users. In summary, SQL Server 2025 continues the product’s legacy of top-notch security by incorporating modern identity and encryption practices. By embracing Azure AD, managed identities, and stronger cryptography by default, it helps organizations avoid vulnerabilities and meet compliance requirements more easily, protecting data both at rest and in motion. Mission critical database engine SQL Server 2025 introduces significant performance and reliability enhancements designed to optimize workload efficiency and reduce troubleshooting efforts. Utilize insights gained from prior executions of expressions within queries enhance the performance of future executions. Optional parameter plan optimization helps SQL Server choose the optimal execution plan based on runtime parameter values, reducing performance issues caused by parameter sniffing. Optimized locking improves concurrency by avoiding blocking and lock escalation and reduces lock memory usage. Enhancements in batch mode processing and columnstore indexes further improve SQL Server as a mission-critical database for analytical workloads. Query Store for readable secondaries allows you to monitor and adjust the performance of read-only workloads executing against secondary replicas. In SQL Server 2025 this is enabled by default. Persisted temporary statistics for readable secondaries are now saved to the primary replica, ensuring permanence and avoiding recreation after restarts, which could degrade performance. A new query hint blocks future execution of problematic queries, such as nonessential queries affecting application performance. Optimized Halloween protection reduces tempdb space consumption and improves performance of data modification queries. Tempdb space resource governance improves reliability by restricting workloads from consuming excessive tempdb space. Accelerated database recovery in tempdb provides instantaneous transaction rollback and aggressive log truncation for transactions in tempdb. Fast failover for persistent health issues: The Windows Failover Cluster (WSFC) can be configured to failover the availability group resource promptly upon detection of a persistent health issue for example long I/O . Enhancements have been made to the undo-of-redo process during disaster recovery failover to asynchronous replicas, improving synchronization performance. Internal synchronization mechanisms have been improved to reduce network saturation when the global primary and forwarder replicas are in asynchronous commit mode. Improved health check time-out diagnostics. Configure a distributed availability group between two contained availability groups. The new backup compression algorithm, ZSTD, provides significant enhancements in compression efficiency while utilizing fewer resources. You can now offload FULL, DIFFERENTIAL, and T-LOG backups to a secondary replica in an Always On Availability Group, freeing your primary replica to handle production workloads. Fabric integration and Analytics Database mirroring to Fabric can continuously replicate data from a database in a SQL Server 2025 instance, on-premises or in virtual machines. A mirrored database item is a read-only, continuously replicated copy of your SQL Server database data in OneLake. SQL Server now natively supports querying CSV, Parquet, and Delta files using OPENROWSET, CREATE EXTERNAL TABLE, or CREATE EXTERNAL TABLE commands, without needing PolyBase Query Service. SQL Server on Linux tmfs filesystem is supported for tempdb in SQL Server 2025 on Linux. This enhancement can improve performance for tempdb-heavy workloads by utilizing memory (RAM) instead of disk-based filesystems. Custom password policy enforces a custom password policy for SQL authentication logins in SQL Server on Linux. PolyBase in SQL Server for Linux can now connect to ODBC data sources. Discontinued services Data Quality Services (DQS) is discontinued in this version of SQL Server. We continue to support DQS in SQL Server 2022 (16.x) and earlier versions. Master Data Services (MDS) is discontinued in this version of SQL Server. We continue to support MDS in SQL Server 2022 (16.x) and earlier versions. Get started SQL Server 2025 is not just an iterative update; it’s a substantial upgrade that bridges the worlds of databases and AI, on-premises and cloud. It retains full support for existing applications and T-SQL code, so upgrades can be done with minimal changes. By adopting SQL Server 2025, organizations can answer new questions with their data, serve applications at a greater scale, and integrate more closely with modern data platforms – all while relying on the familiar, reliable foundation that SQL Server has provided for years. Ready to try it out? Get started today: aka.ms/getsqlserver2025. Learn more Microsoft Build 2025: SQL Server 2025: The Database Developer Reimagined Docs: aka.ms/Build/sql2025docs Announcement blog: aka.ms/sqlserver2025 SQL Server homepage: https://www.microsoft.com/en-us/sql-server MSSQL Extension for Visual Studio Code with GitHub Copilot: https://aka.ms/vscode-mssql-copilot
Announcing SQLCon 2026: Better Together with FabCon!
We’re thrilled to unveil SQLCon 2026, the premier Microsoft SQL Community Conference, co-located with the Microsoft Fabric Community Conference (FabCon) from March 16–20, 2026! This year, we’re bringing the best of both worlds under one roof—uniting the vibrant SQL and Fabric communities for a truly next-level experience. Whether you’re passionate about SQL Server, Azure SQL, SQL in Fabric, SQL Tools, migration and modernization, database security, or building AI-powered apps with SQL, SQLCon 2026 has you covered. Dive into 50+ breakout sessions and 4 expert-led workshops designed to help you optimize, innovate, and connect. Why are SQLCon + FabCon better together? One registration, double the value: Register for either conference and get full access to both—mix and match sessions, keynotes, and community events to fit your interests. Shared spaces, shared energy: Enjoy the same expo hall, registration desk, conference app, and community lounge. Network with peers across the data platform spectrum. Unforgettable experiences: Join us for both keynotes at the State Farm Arena and celebrate at the legendary attendee party at the Georgia Aquarium. Our goal is to reignite the SQL Community spirit—restoring the robust networks, friendships, and career-building opportunities that make this ecosystem so special. SQLCon is just the beginning of a renewed commitment to connect at conferences, user groups, online, and at regional events. Early Access Pricing Extended! Register by November 14th and save $200 with code SQLCMTY200. Register Now! Want to share your expertise? The Call for Content is open until November 20th for both conferences! Let’s build the future of data—together. See you at SQLCon + FabCon!SQL + AI: Get ready for a fun new experience, launching next week!
The SQL community is leveling up! We’re launching a lightweight, beginner friendly SQL + AI contest designed to spark awareness of SQL Server 2025’s new AI capabilities—from connecting to an AI model, to generating embeddings, to exploring what’s possible when natural language intelligence meets your database. Building on the momentum, each week in February unlocks a new chapter of the story - from your first steps connecting SQL to AI, to exploring embeddings, to experimenting with lightweight RAG patterns, and finally orchestrating full end-to-end workflows. This will be hands-on, guided, and fun! You don’t need to be an AI expert to participate. Each challenge builds on the last, helping you discover what’s possible when SQL’s new capabilities meet real world scenarios — all in a fun, approachable format designed to spark curiosity and get people talking. Join us for some SQL fun starting next week, February 5th! Stay tuned to this post for more details! Get ready to build, discover, and play. SQL + AI is here.
Announcing General Availability of the mssql-python Driver
We’re thrilled to announce that the mssql-python driver is now Generally Available! 🎉 This milestone marks a major step forward in delivering a modern, high-performance, and developer-friendly experience for Python developers working with SQL Server, Azure SQL and SQL databases in Fabric. Why mssql-python? The mssql-python driver is a DB-API 2.0 compliant driver designed from the ground up to provide speed, simplicity, and security for Python applications connecting to SQL Server. We think data and devops engineers, analysts, and developers who use Python for configuration, analysis or AI will all find something they like. Here’s what makes it stand out: 🚀 Fast and Cross-platform The mssql-python driver is built on an optimized C++ core that delivers high performance and a consistent API across operating systems. Internal benchmarks show that the mssql-python driver performs well across common SQL operations such as SELECT, INSERT, UPDATE, and DELETE. Complex queries, joins, and stored procedures also perform well, making it ideal for both transactional and analytical workloads. 📦 One-Line Installation Whether you are just getting started or sharing scripts you have written, the mssql_python driver makes it easier than ever. Install the driver with a single command: pip install mssql-python No extra dependencies on Windows, no complicated configurations - just install and start coding. 🔐 Simplified Entra ID Authentication Security shouldn’t be hard. The mssql-python driver offers built-in support for Microsoft Entra ID (formerly Azure AD) authentication, reducing complexity and eliminating the need for custom token handling. This makes it easier to build secure, enterprise-grade applications without extra overhead. The mssql-python driver supports Active Directory Default authentication across all operating systems, making it easier to remove credentials from your code while still allowing you to share a script that just works. Key Highlights Cross-Platform Support: Works seamlessly on Windows, Linux, and macOS (including Apple Silicon). Connection Pooling: Efficient, configurable pooling for high-performance applications. Modern Python Experience: Clean APIs, better diagnostics, and improved error handling. Get Started Today Upgrade your Python data workflows with the new mssql-python driver: pip install mssql-python Check out the GitHub repository for documentation, examples, and to join the community. You can also go directly to our PyPI page to download the latest release. Visit the aka.ms/mssql-python#get-started to view more quickstarts. What’s Next? We’re committed to continuous improvement. Upcoming releases will focus on bulk insert optimizations, ORM integrations, and community-driven enhancements. Stay tuned for updates and share your feedback on GitHub!
Resource governor - a new beginning
Executive summary In addition to increased CPU and memory limits, we are making another change to benefit customers using the SQL Server Standard edition. Starting with SQL Server 2025, resource governor, previously an Enterprise edition feature, is also available in the Standard edition. A powerful tool Resource governor has been a part of SQL Server for more than 15 years. It’s a powerful, full-featured tool that improves reliability when multiple applications or users share resources on the same SQL Server instance. We rely on Resource Governor to isolate workloads on our SQL Server instances by controlling CPU and memory usage. It helps us ensure that the core of our trading systems remains stable and runs with predictable performance, even when other parts of the systems share the same servers. - Ola Hallengren, Chief Data Platforms Engineer at Saxo Bank and a Data Platform MVP Yet when we ask customers if they use resource governor, a frequent answer is "We can't. We are on Standard edition." Indeed, ever since its initial release, resource governor has been an Enterprise-only feature. That made it less known and less commonly used than it deserves. We heard and acted on your feedback. Starting with SQL Server 2025, resource governor is available in both Standard and Enterprise editions, with identical capabilities. This includes the respective Developer editions as well. In Azure SQL Managed Instance, resource governor is already available in all service tiers. What can it do? Here are just some of the things you can accomplish using resource governor: Limit or reserve CPU bandwidth and IOPS for a workload. Limit the size of query memory grants or reserve memory for query processing. Limit the total number of running requests (queries) for a workload. Abort query batches that exceed a specified amount of CPU time. Set a hard cap on the maximum degree of parallelism (MAXDOP) for queries. (New in SQL Server 2025) Limit the amount of tempdb space a workload can use (blog | doc). Whether you are on Standard or Enterprise edition, if you haven't used resource governor yet, see what it can do for you. To help you learn, we have a new step-by-step guide with best practices and examples, from simple to more advanced. There is also a separate guide focusing on the new tempdb space governance feature. Conclusion With this change, customers on Standard edition get a powerful enterprise-grade tool to control resource contention and improve reliability of their SQL Server environments. We encourage you to learn more about resource governor to understand the full range of its capabilities. Have questions or feedback? Post a comment on this blog post, an idea at https://aka.ms/sqlfeedback, or email us at sql-rg-feedback@microsoft.com. Let’s make resource governor a standard (😊) tool in your toolset!SQL Server 2025: introducing optimized Halloween protection
Executive summary Optimized Halloween protection, available in the public preview of SQL Server 2025 starting with the CTP 2.0 release, reduces tempdb space consumption and improves query performance by redesigning the way the database engine solves the Halloween problem. An example in the appendix shows CPU and elapsed time of a query reduced by about 50% while eliminating all tempdb space consumption. Update 2025-09-02 During public preview of SQL Server 2025, we identified a potential data integrity issue that might occur if optimized Halloween protection is enabled. While the probability of encountering this issue is low, we take data integrity seriously. Therefore, we temporarily removed optimized Halloween protection from SQL Server 2025, starting with the RC 0 release. The fix for this issue is in progress. In the coming months, we plan to make optimized Halloween protection available in Azure SQL Database and Azure SQL Managed Instance with the always-up-to-date update policy. Enabling optimized Halloween protection in a future SQL Server 2025 update is under consideration as well. The Halloween problem The Halloween problem, named so because it was discovered on Halloween in 1976, occurs when a data modification language (DML) statement changes data in such a way that the same statement unexpectedly processes the same row more than once. Traditionally, the SQL Server database engine protects DML statements from the Halloween problem by introducing a spool operator in the query plan, or by taking advantage of another blocking operator already present in the plan, such as a sort or a hash match. If a spool operator is used, it creates a temporary copy of the data to be modified before any modifications are made to the data in the table. While the protection spool avoids the Halloween problem, it comes with downsides: The spool requires extra resources: space in tempdb, disk I/O, memory, and CPU. Statement processing by the downstream query operators is blocked until the data is fully written into the spool. The spool adds query plan complexity that can cause the query optimizer to generate a less optimal plan. Optimized Halloween protection removes these downsides by making the spool operator unnecessary. How it works When accelerated database recovery (ADR) is enabled, each statement in a transaction obtains a unique statement identifier, known as nest ID. As each row is modified by a DML statement, it is stamped with the nest ID of the statement. This is required to provide the ACID transaction semantics with ADR. During DML statement processing, when the storage engine reads the data, it skips any row that has the same nest ID as the current DML statement. This means that the query processor doesn't see the rows already processed by the statement, therefore avoiding the Halloween problem. How to use optimized Halloween protection To enable optimized Halloween protection for a database, the following prerequisites are required: ADR must be enabled on the database. The database must use compatibility level 170. The OPTIMIZED_HALLOWEEN_PROTECTION database-scoped configuration must be enabled. The OPTIMIZED_HALLOWEEN_PROTECTION database-scoped configuration is enabled by default. This means that when you enable ADR for a database using compatibility level 170, it will use optimized Halloween protection. You can ensure that a database uses optimized Halloween protection by executing the following statements: ALTER DATABASE [<database-name-placeholder>] SET ACCELERATED_DATABASE_RECOVERY = ON WITH ROLLBACK IMMEDIATE; ALTER DATABASE [<database-name-placeholder>] SET COMPATIBILITY_LEVEL = 170; ALTER DATABASE SCOPED CONFIGURATION SET OPTIMIZED_HALLOWEEN_PROTECTION = ON; You can also enable and disable optimized Halloween protection at the query level by using the ENABLE_OPTIMIZED_HALLOWEEN_PROTECTION and DISABLE_OPTIMIZED_HALLOWEEN_PROTECTION query hints, either directly in the query, or via Query Store hints. These hints work under any compatibility level and take precedence over the OPTIMIZED_HALLOWEEN_PROTECTION database-scoped configuration. When optimized Halloween protection is used for an operator in the query plan, the OptimizedHalloweenProtectionUsed property of the operator in the XML query plan is set to True. For more details, see optimized Halloween protection in documentation. Conclusion Optimized Halloween protection is another Intelligent Query Processing feature that improves query performance and reduces resource consumption when you upgrade to SQL Server 2025, without having to make any changes to your query workloads. We are looking forward to your feedback about this and other features during the public preview of SQL Server 2025 and beyond. You can leave comments on this blog post, email us at intelligentqp@microsoft.com, or leave feedback at https://aka.ms/sqlfeedback. Appendix The following script shows how optimized Halloween protection removes the protection spool in the query plan, and reduces tempdb usage, CPU time, and duration when enabled. /* Requires the WideWorldImporters sample database. SQL Server backup: https://github.com/Microsoft/sql-server-samples/releases/download/wide-world-importers-v1.0/WideWorldImporters-Full.bak Bacpac: https://github.com/Microsoft/sql-server-samples/releases/download/wide-world-importers-v1.0/WideWorldImporters-Standard.bacpac */ /* Ensure that optimized Halloween protection prerequisites are in place */ ALTER DATABASE WideWorldImporters SET ACCELERATED_DATABASE_RECOVERY = ON WITH ROLLBACK IMMEDIATE; ALTER DATABASE WideWorldImporters SET COMPATIBILITY_LEVEL = 170; ALTER DATABASE SCOPED CONFIGURATION SET OPTIMIZED_HALLOWEEN_PROTECTION = ON; GO /* Validate configuration */ SELECT d.compatibility_level, d.is_accelerated_database_recovery_on, dsc.name, dsc.value FROM sys.database_scoped_configurations AS dsc CROSS JOIN sys.databases AS d WHERE dsc.name = 'OPTIMIZED_HALLOWEEN_PROTECTION' AND d.name = DB_NAME(); GO /* Create the test table and add data */ DROP TABLE IF EXISTS dbo.OptimizedHPDemo; BEGIN TRANSACTION; SELECT * INTO dbo.OptimizedHPDemo FROM Sales.Invoices ALTER TABLE dbo.OptimizedHPDemo ADD CONSTRAINT PK_OptimizedHPDemo PRIMARY KEY CLUSTERED (InvoiceID) ON USERDATA; COMMIT; GO /* Ensure that Query Store is enabled and is capturing all queries */ ALTER DATABASE WideWorldImporters SET QUERY_STORE = ON (OPERATION_MODE = READ_WRITE, QUERY_CAPTURE_MODE = ALL); /* Empty Query Store to start with a clean slate */ ALTER DATABASE WideWorldImporters SET QUERY_STORE CLEAR; GO /* Disable optimized Halloween protection as the baseline */ ALTER DATABASE SCOPED CONFIGURATION SET OPTIMIZED_HALLOWEEN_PROTECTION = OFF; GO /* Insert data selecting from the same table. This requires Halloween protection so that the same row cannot be selected and inserted repeatedly. */ BEGIN TRANSACTION; INSERT INTO dbo.OptimizedHPDemo ( InvoiceID, CustomerID, BillToCustomerID, OrderID, DeliveryMethodID, ContactPersonID, AccountsPersonID, SalespersonPersonID, PackedByPersonID, InvoiceDate, CustomerPurchaseOrderNumber, IsCreditNote, CreditNoteReason, Comments, DeliveryInstructions, InternalComments, TotalDryItems, TotalChillerItems, DeliveryRun, RunPosition, ReturnedDeliveryData, ConfirmedDeliveryTime, ConfirmedReceivedBy, LastEditedBy, LastEditedWhen ) SELECT InvoiceID + 1000000 AS InvoiceID, CustomerID, BillToCustomerID, OrderID, DeliveryMethodID, ContactPersonID, AccountsPersonID, SalespersonPersonID, PackedByPersonID, InvoiceDate, CustomerPurchaseOrderNumber, IsCreditNote, CreditNoteReason, Comments, DeliveryInstructions, InternalComments, TotalDryItems, TotalChillerItems, DeliveryRun, RunPosition, ReturnedDeliveryData, ConfirmedDeliveryTime, ConfirmedReceivedBy, LastEditedBy, LastEditedWhen FROM dbo.OptimizedHPDemo; ROLLBACK; GO /* Enable optimized Halloween protection. Execute the following statement in its own batch. */ ALTER DATABASE SCOPED CONFIGURATION SET OPTIMIZED_HALLOWEEN_PROTECTION = ON; GO /* Execute the same query again */ BEGIN TRANSACTION; INSERT INTO dbo.OptimizedHPDemo ( InvoiceID, CustomerID, BillToCustomerID, OrderID, DeliveryMethodID, ContactPersonID, AccountsPersonID, SalespersonPersonID, PackedByPersonID, InvoiceDate, CustomerPurchaseOrderNumber, IsCreditNote, CreditNoteReason, Comments, DeliveryInstructions, InternalComments, TotalDryItems, TotalChillerItems, DeliveryRun, RunPosition, ReturnedDeliveryData, ConfirmedDeliveryTime, ConfirmedReceivedBy, LastEditedBy, LastEditedWhen ) SELECT InvoiceID + 1000000 AS InvoiceID, CustomerID, BillToCustomerID, OrderID, DeliveryMethodID, ContactPersonID, AccountsPersonID, SalespersonPersonID, PackedByPersonID, InvoiceDate, CustomerPurchaseOrderNumber, IsCreditNote, CreditNoteReason, Comments, DeliveryInstructions, InternalComments, TotalDryItems, TotalChillerItems, DeliveryRun, RunPosition, ReturnedDeliveryData, ConfirmedDeliveryTime, ConfirmedReceivedBy, LastEditedBy, LastEditedWhen FROM dbo.OptimizedHPDemo; ROLLBACK; GO /* Examine query runtime statistics and plans for the two executions of the same query. */ SELECT q.query_id, q.query_hash, qt.query_sql_text, p.plan_id, rs.count_executions, rs.avg_tempdb_space_used * 8 / 1024. AS tempdb_space_mb, FORMAT(rs.avg_cpu_time / 1000., 'N0') AS avg_cpu_time_ms, FORMAT(rs.avg_duration / 1000., 'N0') AS avg_duration_ms, TRY_CAST(p.query_plan AS xml) AS xml_query_plan FROM sys.query_store_runtime_stats AS rs INNER JOIN sys.query_store_plan AS p ON rs.plan_id = p.plan_id INNER JOIN sys.query_store_query AS q ON p.query_id = q.query_id INNER JOIN sys.query_store_query_text AS qt ON q.query_text_id = qt.query_text_id WHERE q.query_hash = 0xC6ADB023512BBCCC; /* For the second execution with optimized Halloween protection: 1. tempdb space usage is zero 2. CPU time and duration are reduced by about 50% 3. The Clustered Index Insert operator in the query plan has the OptimizedHalloweenProtection property set to True */Introducing optimized locking v2
Executive summary New improvements in optimized locking further reduce the overhead of locks in the MSSQL database engine. For many transactions, row and page locks aren’t taken at all while still retaining ACID transaction semantics. The improvements require no changes in customer workloads or configuration and are a part of optimized locking in SQL Server 2025, Azure SQL Database, SQL database in Fabric, and Azure SQL Managed Instance. Optimized locking recap Optimized locking was originally released in Azure SQL Database in 2023. The feature has two components: Transaction ID (TID) locking Lock After Qualification (LAQ) With TID locking, while individual row and page locks are still taken, they are not held until the end of transaction because the transaction remains protected by a single TID lock. Concurrency is improved because lock escalation is much less likely to occur. Memory usage is also improved because locks are released soon after they are acquired. With LAQ, locks are taken just before a qualified row is modified. This optimistic locking strategy improves concurrency because locks aren’t held while qualifying rows for modification. At Infios, we are very excited about several new features in SQL Server 2025 and the vast amount of opportunities for performance improvements. We are most excited about the optimized locking feature and how that can drastically help reduce locking across our customers and all their unique workloads. - Tim Radney, SaaS Operations Manager at Infios and a Data Platform MVP Improvements In recent months, we have made two improvements that make a database more lock-free and make the benefits of optimized locking available to more workloads: Skip index locks (SIL) Query plan LAQ feedback persistence These improvements are in effect if read committed snapshot isolation (RCSI) is enabled for the database, which is the default in Azure SQL Database and SQL database in Fabric. To gain the most benefit from optimized locking, enable RCSI. Skip index locks With TID locking, lock escalation typically doesn’t occur because locks are released fast enough to avoid crossing the escalation threshold. A large transaction that modifies many rows without lock escalation must acquire and release many locks. These locks don’t consume a lot of memory because they are released quickly. However, each lock acquisition and release requires a call into the Lock Manager component within the engine. Cumulatively for a large transaction, the overhead of these calls might be significant. The SIL improvement reduces this overhead by skipping row and page locks when they are not required to guarantee ACID semantics. When transactions are protected by TID locks, and when RCSI and LAQ are used, an exclusive lock on a modified row is only necessary if there might be other queries accessing the row and expecting it to be stable. Examples of such queries are those that use the Repeatable Read or Serializable isolation levels, or the corresponding locking hints. We call such queries Row Locking Queries, or RLQ. In the SIL improvement, the engine was modified to maintain a special No-RLQ bit for each page in the buffer pool. This bit indicates the absence of RLQ queries accessing any row on the page. When this bit is set, a DML transaction can skip taking row and page locks and instead modify a row with just an exclusive page latch. Based on the Azure SQL Database telemetry, RLQ queries are uncommon in workloads using RCSI or snapshot isolation transactions. Telemetry also tells us that at least half of all DML queries, on average, use LAQ. This indicates that many workloads can benefit from the SIL improvement. Query plan LAQ feedback persistence LAQ uses an optimistic locking strategy. Locks are taken only after a row is qualified for modification, not while qualifying the row. This means that statement processing might need to be internally restarted if another transaction modified the row after it was read but before it was modified by the current transaction. If statement restarts happen frequently, the use of LAQ might introduce a noticeable overhead because the work to process the DML statement needs to be redone. The engine tracks the potentially wasted work and statement restarts. In the original version of optimized locking, this data is aggregated across all statements and tracked in memory at the database level. If the potentially wasted work or statement restarts exceed thresholds, LAQ is disabled for the entire database, and re-enabled if the potentially wasted work and restarts go below the thresholds. With the new improvement, in addition to tracking at the database level, the engine also tracks LAQ feedback at the query plan level and persists it in Query Store. If thresholds are exceeded for a particular query plan, LAQ is disabled only for that plan rather than for the entire database. The rest of the workload still benefits from LAQ. Skipping locks – a demo To demonstrate the SIL improvement, we used SQL Server 2025 to run a workload that executes an UPDATE statement 100 times in a loop. Each statement updates a random number of rows in a table with a clustered index. We used an extended events session with a histogram target to collect the lock_acquired event. Each histogram bucket counts the number of acquired locks for a specific resource type, including KEY and PAGE. Here are the results: For this execution of the demo, 99.6% of key locks and 79% of page locks are skipped. For details, see the Appendix later in this post. Improvement at the Azure scale To zoom out and demonstrate the SIL improvement broadly, the next chart summarizes telemetry data for about 25K databases in Azure SQL Database. The chart shows the ratio of the total skipped to total acquired locks by index type. Broadly, the improvement is most pronounced for nonclustered indexes, where 81% of locks are skipped. Conclusion Improvements in optimized locking show our continuing investment in this core database engine feature. We fine-tuned optimized locking beyond an already successful v1 release and further reduced the overhead of locks. For more information about these two improvements, see Skip index locks and LAQ heuristics. As of this writing, the improvements are enabled in SQL Server 2025 and for most databases in Azure SQL Database and SQL database in Fabric. The rollout to the remainder of the Azure SQL fleet including Azure SQL Managed Instance (with the always-up-to-date and SQL Server 2025 update policy) is in progress. Appendix Here are the T-SQL scripts to demonstrate SIL in action. Demo setup: /* /* Reset the demo */ USE tempdb; ALTER DATABASE olv2 SET SINGLE_USER WITH ROLLBACK IMMEDIATE; DROP DATABASE IF EXISTS olv2; */ CREATE DATABASE olv2; GO USE olv2; /* Enable RCSI, ADR, and optimized locking */ ALTER DATABASE olv2 SET READ_COMMITTED_SNAPSHOT ON WITH ROLLBACK IMMEDIATE; ALTER DATABASE olv2 SET ACCELERATED_DATABASE_RECOVERY = ON WITH ROLLBACK IMMEDIATE; ALTER DATABASE olv2 SET OPTIMIZED_LOCKING = ON WITH ROLLBACK IMMEDIATE; /* Create a sequence to generate clustered index keys */ CREATE SEQUENCE dbo.s_id AS int START WITH 1 INCREMENT BY 1; /* Create a test table */ CREATE TABLE dbo.t ( id int NOT NULL CONSTRAINT df_t_id DEFAULT (NEXT VALUE FOR dbo.s_id), dt datetime2 NOT NULL CONSTRAINT df_t_dt DEFAULT (SYSDATETIME()), u uniqueidentifier NOT NULL CONSTRAINT df_t_uid DEFAULT (NEWID()), s nchar(40) NOT NULL CONSTRAINT df_t_s DEFAULT (REPLICATE('c', 1 + 39 * RAND())), CONSTRAINT pk_t PRIMARY KEY (id) ); /* Insert 50,000 rows */ INSERT INTO dbo.t (s) SELECT REPLICATE('olv2', 10) AS s FROM GENERATE_SERIES(1, 50000); GO /* Create a stored procedure that updates a random number of rows */ CREATE OR ALTER PROCEDURE dbo.update_rows AS SET NOCOUNT, XACT_ABORT ON; /* Get the maximum key value for the clustered index */ DECLARE @MaxKey int = ( SELECT CAST(current_value AS int) FROM sys.sequences WHERE name = 's_id' AND SCHEMA_NAME(schema_id) = 'dbo' ); /* Get a random key value within the key range */ DECLARE @StartKey int = 1 + RAND(CAST(CAST(NEWID() AS varbinary(3)) AS int)) * @MaxKey; /* Get a random number of rows between 1 and 500 */ DECLARE @RowCount int = 1 + RAND() * 499; /* Update rows */ UPDATE TOP (@RowCount) dbo.t SET dt = DEFAULT, u = DEFAULT, s = DEFAULT WHERE id >= @StartKey; GO /* Create an event session to collect lock statistics */ IF EXISTS ( SELECT 1 FROM sys.server_event_sessions WHERE name = N'olv2_locks' ) DROP EVENT SESSION olv2_locks ON SERVER; CREATE EVENT SESSION olv2_locks ON SERVER ADD EVENT sqlserver.lock_acquired ( SET collect_database_name = 1 WHERE database_name = N'olv2' ) ADD TARGET package0.histogram ( SET filtering_event_name = N'sqlserver.lock_acquired', source = N'resource_type', source_type = 0 ); GO Execute the workload and collect a histogram of locks by resource type: USE olv2; ALTER EVENT SESSION olv2_locks ON SERVER STATE = START; GO EXEC dbo.update_rows; GO 100 WITH histogram_target AS ( SELECT TRY_CAST(st.target_data AS xml) AS target_data FROM sys.dm_xe_sessions AS s INNER JOIN sys.dm_xe_session_targets AS st ON s.address = st.event_session_address WHERE s.name = 'olv2_locks' ), lock_type_histogram AS ( SELECT hb.slot.value('(@count)[1]', 'bigint') AS slot_count, hb.slot.value('(value/text())[1]', 'int') AS lock_type FROM histogram_target AS ht CROSS APPLY ht.target_data.nodes('/HistogramTarget/Slot') AS hb(slot) ) SELECT mv.map_value AS lock_type_desc, lth.slot_count AS lock_acquired_count FROM lock_type_histogram AS lth INNER JOIN sys.dm_xe_map_values AS mv ON lth.lock_type = mv.map_key WHERE mv.name = 'lock_resource_type' ORDER BY lock_type_desc; ALTER EVENT SESSION olv2_locks ON SERVER STATE = STOP; GO Each workload run can produce slightly different results because other activities (query compilation, file growth, page splits, etc.) also take locks if they occur during the run. However, in this demo, the number of key locks with SIL enabled is always reduced. For comparison purposes, we used an undocumented and unsupported trace flag 7194 to disable SIL. To reenable SIL, disable this trace flag and then rerun ALTER DATABASE … SET OPTIMIZED_LOCKING = ON statement, or restart the database.
