SQL Server 2025: Deeply Integrated and Feature-rich on Linux
SQL Server continues to power mission-critical workloads across enterprises, and with SQL Server 2025, we’re delivering innovations that redefine performance, security, developer experience, AI innovation and flexibility along with additional features tailored for Linux environments. Momentum on SQL Server for Linux The adoption of SQL Server on Linux has been phenomenal. The public preview of SQL Server 2025 has seen remarkable adoption, with Linux based deployments experiencing substantial growth reflecting strong demand for cross-platform capabilities. Enterprises are embracing Linux for cloud native architectures, containers, and Kubernetes deployments and SQL Server is meeting them where they are, enabling customers to run their modern production workloads seamlessly. We’ve collaborated closely with partners such as Canonical, DH2i, PortWorx, and Red Hat (listed alphabetically) to ensure support for the latest distributions and maintain robust high-availability solutions through clustering stacks provided by our partners What’s new in SQL Server 2025 on Linux Here are the highlights: Security Enhancements TLS 1.3 Support for stronger encryption option for data that is transmitted across a network between the client application and SQL Server instance. For details, refer: Encrypt Connections to SQL Server on Linux - SQL Server | Microsoft Learn Ability to Configure Custom password policies via Active Directory (adutil) or mssql.conf for non-domain setups. This allows you to define parameters like minimum password length similar to Windows domain policies whether or not your SQL Server instance on Linux is domain joined. This upgrade gives SQL Server authentication the flexibility and security that enterprises need. Learn more here: Use Custom Password Policy for SQL Logins on Linux - SQL Server | Microsoft Learn Container Images for SQL Server 2025 are now signed to ensure image integrity. Expanded Platform Support Preview support for RHEL 10 and Ubuntu 24.04, expanding enterprise Linux coverage to include support for latest releases from Red Hat and Canonical. For details refer: Get Started with SQL Server 2025 on RHEL 10- preview and Get started with SQL Server 2025 on Ubuntu 24.04- Preview Starting with SQL Server 2025, SUSE Linux Enterprise Server (SLES) is not supported. If you are currently using SQL Server 2022 or an earlier version on SLES, you will continue to receive cumulative updates and support as outlined in the SQL Server 2022 Lifecycle policy or the relevant policies for earlier versions, with no changes to your existing experience for existing deployments. To upgrade to SQL Server 2025, back up your databases and restore them to a supported distribution. Performance Optimizations Tmpfs Support for SQL Server on Linux: For SQL Server on Linux running on physical machines, virtual machines, or containers, you can now host tempdb data and log files on the tmpfs filesystem. This enhancement significantly improves performance for workloads prone to tempdb disk spills, delivering faster throughput and efficiency in this scenario. For containers-based SQL deployment, you can also host all data and log files including user and system database on the tmpfs filesystem, delivering ultra-fast I/O for development and testing scenarios. However, note that data stored on tmpfs is ephemeral and will be lost when the container restarts. Therefore, only use this option for databases where data loss after restart is acceptable, such as in development or test environments. Learn more about tmpfs support here: Enable and Run tempdb on tmpfs for SQL Server 2025 on Linux - SQL Server | Microsoft Learn Advanced Analytics Generic ODBC Data Source Support with PolyBase Seamlessly query external data sources from Linux-based SQL Server using bring your own driver (BYOD) similar to SQL Server on Windows. This feature uses an external service to securely isolate and load drivers, ensuring safe usage. For details refer: Use ODBC Data Source with SQL Server on Linux - SQL Server | Microsoft Learn Developer Experience VS Code – SQL Server (mssql) Extension: Deploy SQL Server 2025 local containers directly from Visual Studio Code using the SQL Server (mssql) extension for a streamlined developer workflow. For details refer: SQL Server (mssql) - Visual Studio Marketplace Validated Pattern with Red Hat We’ve partnered with Red Hat to deliver a validated deployment pattern for SQL Server on RHEL Supercharging Financial Insights with RAG-Based Search on Microsoft SQL Server. The validated patterns are an advanced form of reference architecture, offering a streamlined approach to deploying complex business solutions. To learn more about Validated patterns and how it's different from traditional reference architecture please refer: About Validated Patterns | Validated Patterns. Quotes from our partners: "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 "The availability of SQL Server 2025 on Ubuntu 24.04 provides developers and enterprises a robust foundation for building and deploying demanding AI-driven applications." Jehudi Castro-Sierra, Public Cloud Alliance Director, Canonical “As a leading provider of high availability and database management software, we're thrilled about the performance enhancements and features added to SQL Server 2025. New capabilities like Vector Search and AI-powered optimization will allow our customers to drive business success through data-driven decision-making, faster query execution, improved throughput, and reduced downtime. The automated tuning and maintenance capabilities will also significantly improve operational efficiency, and reduce the complexity and cost associated with database management. Our participation in the SQL Server 2025 EAP has allowed us to ensure that we will provide comprehensive high availability support for our customers’ mission-critical database deployments of SQL Server 2025, including native TLS 1.3 support for encrypted communications, ensuring modern, secure, and high-performance connectivity across all environments. Whether our customers are deploying native or containerized instances on Windows or Linux, DH2i software solutions will ensure nearest-to-zero downtime and fully automatic failover. Additionally, we will be ready to provide secure and intelligent HA for the complex, cross-platform data estates that our customers will be building to support their SQL Server 2025-backed AI applications.” -OJ Ngo, Co-Founder & CTO, DH2i Learn More Explore the full list of features: What's New for SQL Server 2025 Preview on Linux - SQL Server | Microsoft Learn Join us at Microsoft Ignite for deep-dive sessions and demos.Unlocking Enterprise AI: SQL Server 2025 and NVIDIA Nemotron RAG Accelerate AI
Today, most of the world’s data still remains untapped, sitting in databases, documents, and systems across organizations. Enterprises are racing to unlock this data’s value by building the next wave of generative AI applications—solutions that can answer questions, summarize documents, and drive smarter decisions. At the heart of these innovations are retrieval-augmented generation (RAG) pipelines, which enable users to interactively engage with large amount of data that continuously evolves. Yet, as promising as RAG pipelines are, enterprises face real challenges in making them work at scale. Handling both structured and unstructured data, processing massive volumes efficiently, and ensuring privacy and security are just a few hurdles. This is where the integration between SQL Server 2025 and NVIDIA Nemotron RAG models, deployed as NVIDIA NIM microservices, comes in, offering a new approach that streamlines AI deployment and delivers enterprise-grade performance—whether you’re running workloads in the cloud or on-premises. “As AI becomes core to every enterprise, organizations need efficient and compliant ways to bring intelligence to their data,” said Joey Conway, Senior Director of Generative AI software at NVIDIA. “With SQL Server 2025’s built-in AI and NVIDIA Nemotron RAG, deployed as NIM microservices, enterprises can deploy and run AI models close to their data on premises or in the cloud without complex integration, accelerating innovation while maintaining data sovereignty and control.” Overcoming the complexity of generating embeddings at scale Customer challenge Building responsive AI applications using RAG requires converting SQL data into vector embeddings—a process that feeds huge amounts of text through complex neural networks. This is inherently parallel and compute-intensive, often creating performance bottlenecks that prevent real-time data indexing. The result? Slow applications and poor user experiences. Moreover, enterprises need flexibility. Different embedding models excel at different tasks—semantic search, recommendations, classification—and each comes with its own tradeoffs in accuracy, speed, and cost. Businesses want to mix and match models, balance premium performance with budget constraints, and stay resilient against model deprecation or API changes. Furthermore, rapid experimentation and adaptation are key to staying ahead and thus developers want models that offer flexible customization and full transparency. The Solution: SQL Server 2025 + NVIDIA Nemotron RAG SQL Server 2025 brings AI closer to your data, allowing you to natively and securely connect to any model hosted anywhere. You can generate embeddings directly in SQL using extensions to T-SQL —no need for new languages, frameworks, or third-party tools. By connecting SQL Server 2025 to the llama-nemotron-embed-1b-v2 embedding model from NVIDIA, you eliminate bottlenecks and deliver the massive throughput needed for real-time embedding generation. llama-nemotron-embed-1b-v2 is a best in class embedding model that offers multilingual and cross-lingual text question-answering retrieval with long context support and optimized data storage. This model is part of NVIDIA Nemotron RAG models, a collection of extraction, embedding, reranking models, fine-tuned with the Nemotron RAG datasets and scripts, to achieve the best accuracy. These models offer flexible customization, enabling easy fine-tuning and rapid experimentation. They also offer full transparency with open access to models, datasets, and scripts. Llama-nemotron-embed-1b-v2 is the model of choice for embedding workflows, but this high-speed inference pipeline is not limited to this model and can potentially call any optimized AI model as an NVIDIA NIM microservice, seamlessly powering every stage of the RAG pipeline. From multimodal data ingestion and advanced retrieval to reranking, all operations run directly on your data within SQL Server. Such RAG systems can be applied across a wide range of use cases, enabling intelligent, context-aware applications across industries. Customer Benefits: With GPU acceleration and built-in AI of SQL Server 2025, you can achieve optimal inference, ensuring performance that meets the demands of modern applications. Our flexible approach lets you mix and match models to suit different use cases, striking the right balance between accuracy and cost. And with open models that enable vendor flexibility and rapid adaptation, you gain resilience to stay ahead of the curve in an ever-changing AI landscape. Streamlining AI Model Deployment with Enterprise-Grade Confidence Customer Challenge Integrating advanced AI models into enterprise workflows has historically been slow and complex. Specialized teams must manage intricate software dependencies, configure infrastructure, and handle ongoing maintenance—all while navigating the risks of deploying unsupported models in mission-critical environments. This complexity slows innovation, drains engineering resources, and increases risk. The Solution: Simplified, Secure Model Deployment with NVIDIA NIM This collaboration simplifies and de-risks AI deployment. The llama-nemotron-embed-1b-v2 model is available as an NVIDIA NIM microservice for secure, reliable deployment across multiple Azure compute platforms. Prebuilt NIM containers for a broad spectrum of AI models and can be deployed with a single command for easy integration into enterprise-grade AI applications using built-in REST APIs of SQL Server 2025 and just a few lines of code, regardless where you run SQL Server workloads and NVIDIA NIM, on premises or in the cloud. NIM containers package the latest AI models together with the best inference technology from NVIDIA and the community and all dependencies into a ready-to-run container, abstracting away the complexity of environment setup so customers can spin up AI services quickly. Furthermore, NVIDIA NIM is enterprise-grade and is continuously managed by NVIDIA with dedicated software branches, rigorous validation processes, and support. As a result, developers can confidently integrate state-of-the-art AI into their data applications. This streamlined approach significantly reduces development overhead and provides the reliability needed for mission-critical enterprise systems. NVIDIA NIM containers are discoverable and deployable via Microsoft Azure AI Foundry’s model catalog. Customer Benefits Rapid deployment with minimal setup means you can start leveraging AI without specialized engineering, and SQL Server 2025 makes it even easier with built-in support for AI workloads and native REST APIs. Enterprise-grade security and monitoring ensure safe, reliable operations, while SQL Server’s integration with Entra ID and advanced compliance features provide added protection. Direct integration into SQL workflows reduces complexity and risk, and with SQL Server’s hybrid flexibility, you can run seamlessly across on-premises and cloud environments—simplifying modernization while maintaining control. Innovating Without Compromise on Security or Flexibility Customer Challenge Organizations in regulated industries often face a tough choice: adopt powerful AI or maintain strict data residency and compliance. Moving sensitive data to external services is often not an option, and many companies run AI inference workloads both in the cloud and on-premises to balance scalability, privacy, regulatory compliance, and low-latency requirements. The Solution: Flexible, Secure Integration—On-Premises and Cloud SQL Server 2025 enables organizations in regulated environments to securely integrate locally hosted AI models, ensuring data residency and compliance while minimizing network overhead. This architecture boosts throughput by keeping sensitive data on-premises and leveraging SQL Server’s native extensibility for direct model invocation. With SQL Server 2025 and Nemotron RAG, deployed as NVIDIA NIM microservices, you get the best of both worlds. This solution can be seamlessly deployed in the cloud with serverless NVIDIA GPUs on Azure Container Apps (ACA) or on-premises with NVIDIA GPUs on Azure Local. Sensitive data never leaves your secure environment, allowing you to harness the full power of Nemotron models while maintaining complete data sovereignty and meeting the strictest compliance mandates. Customer Benefits SQL Server 2025 helps you maintain compliance by supporting data residency and meeting regulatory standard requirements across regions. Sensitive data stays protected on-premises with enterprise-grade security, including consistent access controls, ledger support, and advanced encryption to minimize risk. At the same time, SQL Server’s hybrid flexibility lets you deploy AI workloads wherever they’re needed—on-premises, in the cloud, or across a hybrid environment—while leveraging built-in AI features like vector search and secure integration with locally hosted models for performance and control. Conclusion: Powering the Next Wave of Enterprise AI The collaboration between Microsoft and NVIDIA is more than a technical integration. It’s designed to help enterprises overcome the toughest challenges in AI deployment. By streamlining vector embedding and vector search, delivering enterprise-grade performance, and enabling secure, flexible integration across cloud and on-premises environments, this joint solution empowers organizations to unlock the full value of their data. Whether you’re building conversational AI, automating document analysis, or driving predictive insights, SQL Server 2025 and NVIDIA Nemotron RAG models, deployed as NIM, provide the tools you need to innovate with confidence. The future of enterprise AI is here and it’s flexible, secure, and built for real business impact. Get started today: Learn more about SQL Server 2025 and download it today Learn more about our joint solution from NVIDIA’s Technical Blog GitHub: Microsoft SQL Server 2025 and NVIDIA Nemotron RAGData Virtualization with PolyBase for SQL Server 2025
Building upon the innovations introduced in SQL Server 2022, SQL Server 2025 enhances Data Virtualization by prioritizing usability, strengthening security with expanded authentication options, and providing improved support for Linux environments. Key Features Native Support for Parquet, CSV, and Delta: The SQL engine now offers built-in capabilities to query data files such as CSV, Parquet, and Delta, eliminating the need for the optional “PolyBase Query Service for External Data” installation. PolyBase services are required solely when querying external databases. Support for TDS 8: PolyBase in SQL Server 2025 includes support for TDS 8 for connections between SQL Server instances. Managed Identity Support for Arc-enabled SQL Server: With Arc-enabled SQL Server 2025, Managed Identity is now available for use with PolyBase, providing secure connections to Azure Storage Accounts. ODBC Support for Linux: PolyBase on SQL Server 2025 for Linux now supports ODBC data sources, matching Windows functionality. Use Cases Business Insights: Access and analyze distributed data across diverse sources without moving it, enabling faster business intelligence, and reporting. Azure Integration: Seamlessly connect to Azure Storage Accounts, leveraging managed identities for secure cloud access and hybrid scenarios. Data Tiering: Offload cold or infrequently accessed data to external storage like Azure, reducing storage costs while keeping the data available for queries. Simplified ETL and Data Exploration: Streamline Extract, Transform, Load (ETL) and reverse-ETL processes by natively supporting common data formats such as CSV, Parquet, and Delta. Cross-platform Data Access: Achieve parity and flexibility by connecting to ODBC data sources on both Windows and Linux environments. Enhanced Security and Compliance: Strengthen data protection using TDS 8 and managed identities, ensuring secure access to external data. Getting Started SQL Server 2025’s makes data virtualization easier and safer than ever, get started today downloading: SQL Server 2025 Preview Trial To know more about Data Virtualization improvements check, Introducing Data Virtualization with PolyBase - SQL Server | Microsoft LearnMicrosoft SQL Server on Ubuntu pro-The preferred choice for deploying SQL Server on Ubuntu in Azure!
Update as of 29 September 2025: Please note that Option 1, as described in the blog post below, is no longer available following the latest announcement. For full details, refer to the blog titled latest updates to SQL Server on Linux VM provisioning on Azure. Today, you can deploy SQL Server on Ubuntu based Azure virtual machines (VMs) in one of the three ways: Option 1: Use the pre-configured Microsoft SQL Server on Ubuntu Pro Azure marketplace image for the Azure virtual machine(VM) creation. Option 2: Deploy a Azure VM based on an Ubuntu Pro image and then manually install and configure the SQL Server. Option 3: Deploy an Ubuntu LTS image based Azure VM, then manually install and configure SQL Server. In this blog, I'd like to spend some time discussing option 1, which is Microsoft SQL Server on Ubuntu Pro Azure marketplace images which were introduced in November 2021 last year. And, why should you consider this as the preferred alternative? The first question to consider is: What additional capabilities are offered by Ubuntu Pro? To help you answer this question, I’d recommend you to read the below articles published by Canonical, which clearly document the advantages of Ubuntu Pro, such as FIPS & CC-EAL2 certification, open-source security, kernel live patch. Ubuntu Pro for Azure | Ubuntu The benefits of running Microsoft SQL Server on Ubuntu Pro | Ubuntu. Now that you are aware of the benefits of Ubuntu Pro, option 3 is no longer among the preferred options as it does not use Ubuntu pro. As a result, we are left with two options: Option 1 and Option 2. The most important aspect to consider for any production grade database workload is the supportability of the entire solution stack, and this is where option 1 of using pre-configured Microsoft SQL Server on Ubuntu Pro Azure marketplace images gives you an advantage, as the SQL Server Azure VMs deployed on Ubuntu Pro using the above image, are a fully 24/7 supported stack from both Microsoft and Canonical. You can basically open a support ticket through the Azure portal for assistance, and both the Microsoft and Canonical teams will work together to promptly provide you with the required support. When you choose option 2, which is where you first deploy an Ubuntu Pro Azure VM and then manually deploy SQL Server, you still have gaps in your support coverage. Ubuntu Pro is designed to be a cost-effective way to increase the security of your Ubuntu estate and by default does not include any technical support. Technical support can be added to Ubuntu Pro with a private offer or separate support subscription from Canonical, but even so the support will be for the operating system (OS) and the database separately & independent of each other. In contrast, when using the pre-configured SQL Server on Ubuntu Pro marketplace image, you get 24/7 support for the entire stack by default. Hence, the preferred deployment method for a production grade workload deployment for SQL Server on Ubuntu is to use the pre-configured Microsoft SQL Server on Ubuntu Pro Azure marketplace image for creating the SQL Server VMs in Azure. So get started with your production workload deployments on SQL Server on Ubuntu Pro Azure VM using the SQL Server on Ubuntu Pro in Azure Gallery image!!Announcement: Upcoming Changes to SQL Server on Linux Virtual Machine (VM) Provisioning in Azure
We’re making an important update to how customers provision SQL Server on Linux virtual machines (VMs) in Azure. What’s Changing? Starting soon, Linux-based SQL Server Virtual Machine (VM) images published by Microsoft will be removed from the Azure Marketplace. As a result, these SQL Server on Linux images will no longer be visible in the Azure SQL hub during VM provisioning, nor accessible via CLI, Azure Portal, or PowerShell scripts. This change is part of our broader effort to simplify and modernise the provisioning experience for SQL Server Linux on Azure. Why Are We Making This Change? We’re transitioning away from image-based provisioning to a script-based model that offers greater flexibility, automation, and control. This fresh approach will allow customers to: Choose their preferred supported Linux distribution (RHEL, SLES or Ubuntu (Pro)) Select SQL Server version and edition Configure licensing options Customise deployment parameters through scripts and ability to add VM extensions. This shift ensures a more consistent and extensible experience across all supported platforms. When Will This Happen? The deprecation of Linux VM images will begin shortly and will be completed over the next couple of months. During this transition, customers may notice the SQL Server on Linux based Azure marketplace image listings may not be available. What Should You Do? For the Azure Virtual Machines deployed using the SQL on Linux Azure marketplace images in the past they'd continue to work, but if you’re planning to deploy new SQL Server on Linux based Azure Virtual Machines, please follow the below steps: Manual installation is recommended during this transition period. Start by creating a Linux Virtual Machine using the Azure Portal, CLI, or PowerShell. Once the VM is provisioned, follow the official SQL Server installation documentation to complete the setup. VM Creation Guidance: You can refer to this guide for step-by-step instructions on creating an Azure Linux-based virtual machine: https://learn.microsoft.com/en-us/azure/virtual-machines/linux/quick-create-portal Choosing a Linux Distribution: Feel free to select the distribution that best fits your requirements. For a list of endorsed Linux distributions on Azure, see: Linux distributions endorsed on Azure - Azure Virtual Machines | Microsoft Learn Please note, SQL Server is officially supported only on the following Linux distributions. Based on the distribution you choose, refer to the corresponding documentation for SQL Server installation guidance: Red Hat Enterprise Linux (RHEL) SUSE Linux Enterprise Server (SLES) Ubuntu For more details on supported distributions refer to: SQL Server 2025 - Supported Linux distributions SQL Server 2022 - Supported Linux distributions A new script-based provisioning experience is coming soon - stay tuned for announcements. We’ll continue to share updates through the Azure portal, documentation, and this blog.SQL Server 2025 Preview RC1: Now Supporting Red Hat Enterprise Linux (RHEL) 10
We’re happy to announce that SQL Server 2025 Release Candidate 1 (RC1) now includes preview support for Red Hat Enterprise Linux (RHEL) 10, expanding our commitment to modern, secure, and flexible Linux-based deployments. RHEL 10 Support in SQL Server 2025 RC1 You can now deploy SQL Server 2025 Preview on RHEL10 for your Dev/Test environments using the Enterprise Evaluation Edition, which is valid for 180 days. For your production workloads you could use SQL Server 2022 on RHEL 9 or Ubuntu 22.04. Deploying SQL Server 2025 RC1 on RHEL10 You can follow the Quickstart: Install SQL Server and create a database on RHEL10 to install SQL Server and create a database on RHEL10. It walks you through everything—from preparing your system to installing and configuring SQL Server. To explore the latest improvements in SQL Server 2025 RC1, check out What's New in SQL Server 2025 - SQL Server | Microsoft Learn. I was particularly interested in testing the new Half-precision float support in vector data type. To do this, I deployed SQL Server RHEL10 (the tag is 2025-RC1-rhel-10) container on WSL2 and I already have Docker Desktop installed on my local machine to manage containers. I launched the SQL Server 2025 RC1 container, connected to it using SQL Server Management Studio (SSMS), and successfully tested the vector data type enhancement. docker pull mcr.microsoft.com/mssql/rhel/server:2025-RC1-rhel-10 docker run -e "ACCEPT_EULA=Y" -e "MSSQL_SA_PASSWORD=passwordshouldbestrong" \ -e "MSSQL_AGENT_ENABLED=true" \ -p 14337:1433 --name sql2025RC1RHEL10 --hostname sql2025RC1RHEL10 \ -d mcr.microsoft.com/mssql/rhel/server:2025-RC1-rhel-10 SELECT @@VERSION GO CREATE DATABASE SQL2025onRHEL10 GO USE SQL2025onRHEL10 GO -- Step 0: Enable Preview Features ALTER DATABASE SCOPED CONFIGURATION SET PREVIEW_FEATURES = ON; GO -- Step 1: Create a Table with a VECTOR(5, float16) Column CREATE TABLE dbo.Articles ( id INT PRIMARY KEY, title NVARCHAR(100), content NVARCHAR(MAX), embedding VECTOR(5, float16) ); -- Step 2: Insert Sample Data INSERT INTO Articles (id, title, content, embedding) VALUES (1, 'Intro to AI', 'This article introduces AI concepts.', '[0.1, 0.2, 0.3, 0.4, 0.5]'), (2, 'Deep Learning', 'Deep learning is a subset of ML.', '[0.2, 0.1, 0.4, 0.3, 0.6]'), (3, 'Neural Networks', 'Neural networks are powerful models.', '[0.3, 0.3, 0.2, 0.5, 0.1]'), (4, 'Machine Learning Basics', 'ML basics for beginners.', '[0.4, 0.5, 0.1, 0.2, 0.3]'), (5, 'Advanced AI', 'Exploring advanced AI techniques.', '[0.5, 0.4, 0.6, 0.1, 0.2]'); -- Step 3: Perform a Vector Similarity Search Using VECTOR_DISTANCE function DECLARE @v VECTOR(5, float16) = '[0.3, 0.3, 0.3, 0.3, 0.3]'; SELECT TOP (3) id, title, VECTOR_DISTANCE('cosine', @v, embedding) AS distance FROM dbo.Articles ORDER BY distance; -- Step 4: Optionally Create a Vector Index CREATE VECTOR INDEX vec_idx ON Articles(embedding) WITH ( metric = 'cosine', type = 'diskANN' ); -- Step 5: Perform a Vector Similarity Search DECLARE @qv VECTOR(5, float16) = '[0.3, 0.3, 0.3, 0.3, 0.3]'; SELECT t.id, t.title, t.content, s.distance FROM VECTOR_SEARCH( table = Articles AS t, column = embedding, similar_to = @qv, metric = 'cosine', top_n = 3 ) AS s ORDER BY s.distance, t.title; Conclusion The addition of RHEL10 support in SQL Server 2025 Preview is a major milestone in delivering a modern, secure, and flexible data platform for Linux users. We encourage you explore these new capabilities and share your feedback to help us continue enhancing SQL Server for the Linux ecosystem. You can share your feedback using any of the following methods: Email us at sqlpreviewpackage@microsoft.com with your thoughts and suggestions. Submit your ideas on Azure Ideas (Use the SQL Server on Linux Group on the left side of the page) Alternatively, you can open issues related to the preview packages Issues · microsoft/mssql-docker (github.com) on GitHub. We hope you give SQL Server 2025 preview on RHEL10 a try - and we look forward to hearing what you think!SQL Server 2025 Preview: Now Supporting Ubuntu 24.04 and TLS 1.3
We are excited to introduce two key enhancements in the SQL Server 2025 Release Candidate 0 (RC0) for Linux: Ubuntu 24.04 and the addition of Transport Layer Security (TLS) 1.3 support. These updates enable developers, database administrators, and IT professionals to leverage the latest open-source technologies and security protocols, strengthening their data platforms. Ubuntu 24.04 Support in SQL Server 2025 RC0 SQL Server 2025 Preview now supports Ubuntu 24.04. This enables seamless deployment in Dev/Test environments using the Enterprise Evaluation Edition, which is valid for 180 days. Note: Production workloads on Ubuntu 24.04 are not yet supported; for production, use SQL Server 2022 on Ubuntu 22.04 or RHEL 9. How to Deploy SQL Server 2025 RC0 on Ubuntu 24.04 Getting started is easy! You can follow our Quickstart: Install SQL Server and create a database on Ubuntu to walks through everything—from prepping your system to installing and configuring SQL Server on Ubuntu. In this demo, I'll show you how to deploy SQL Server 2025 RC0 on Ubuntu 24.04 running inside WSL2. I've already set up Ubuntu 24.04 on WSL2 and Docker Desktop to manage containers. With just two commands, I was able to launch SQL Server 2025 RC0 in a container. I then connected to it using SQL Server Management Studio (SSMS), where you can see the version information displayed, confirming a successful deployment. lsb_release -a docker pull mcr.microsoft.com/mssql/server:2025-RC0-ubuntu-24.04 docker run -e "ACCEPT_EULA=Y" -e "MSSQL_SA_PASSWORD=<password>" \ -e "MSSQL_AGENT_ENABLED=true" \ -p 14333:1433 --name sql2025preview --hostname sql2025preview \ -d mcr.microsoft.com/mssql/server:2025-RC0-ubuntu-24.04 Here is the snippet of SQL Server ERRORLOG This shows the initial startup messages and confirms the SQL Server version running inside the container. TLS 1.3 Support in SQL Server 2025 RC0 Starting in SQL Server 2025 Preview (RC0), TLS 1.3 is enabled by default. To enable and validate TLS 1.3 for your SQL Server instance, follow the Learn guide: Encrypt Connections to SQL Server on Linux - SQL Server | Microsoft Learn Conclusion The addition of Ubuntu 24.04 and TLS 1.3 support in SQL Server 2025 Preview marks a significant step forward in providing modern, secure, and flexible data platform options. We encourage you to try out these new capabilities and share your feedback as we continue to improve SQL Server for the Linux ecosystem. We recommend you use any of the following options that suits you the best. 1) Send us an email with your feedback to sqlpreviewpackage@microsoft.com. 2) Another option would be to submit your comments directly on Azure Ideas (Use the SQL Server on Linux Group on the left side of the page) 3) Alternatively, you can open issues related to the preview packages Issues · microsoft/mssql-docker (github.com) on GitHub. We hope you give SQL Server 2025 preview on Ubuntu 24.04 a try and let us know what you think!SQL Server on Linux Now Supports cgroup v2
Hello, Linux + SQL Server Fans! If you’re running SQL Server on Linux, here’s some great news - cgroup v2 is now supported in SQL Server 2025 preview and SQL Server 2022 CU 20. This enhancement brings more precise and reliable resource management, especially for containerized deployments in environments like Docker, Kubernetes, and OpenShift. Why cgroup v2 Matters In Linux, control groups (cgroups) are a kernel feature that allows you to allocate, prioritize, and limit system resources such as CPU and memory. With cgroup v2, these capabilities are more unified and robust, offering better enforcement and visibility compared to the older version. To know more please visit: Control Group v2 — The Linux Kernel documentation. How to Check Your cgroup Version Run this command: stat -fc %T /sys/fs/cgroup/ If it returns cgroup2fs, you're using cgroup v2. If it returns cgroup, you're on cgroup v1. How to switch to cgroup v2: The simplest path is choosing a distribution that supports cgroup v2 out of the box. To switch manually: Add to GRUB config: systemd.unified_cgroup_hierarchy=1 Run: sudo update-grub SQL Server and Cgroupv2: Before this update, users running SQL Server containers on Kubernetes clusters (e.g., Azure Kubernetes Service version 1.25 and above) reported that SQL Server did not respect memory limits set via container specs. This led to issues like Out of Memory (OOM) errors, even when limits were properly configured. Here is an example: - For a standard D4ds_v5 machine that has 4 CPUs and 16 GB of RAM as shown in below screenshot If you check the SQL Server errorlog before SQL Server 2022 CU 20: You would observe that SQL Server can see 80% (12792 MB) of the overall memory (16 GB) available on the worker node of the Kubernetes cluster, even though you have configured the 3 Gi memory limit. You ask why just 80% then learn more about the memory.memorylimit, which by default is configured to 80% of the physical memory, to prevent out of memory (OOM) errors. For details please refer: Configure SQL Server Settings on Linux - SQL Server | Microsoft Learn. Below is the errorlog snippet and the container configuration: “Microsoft SQL Server 2022 (RTM-CU19) (KB5054531) - 16.0.4195.2 (X64) Apr 18 2025 13:42:14 Copyright (C) 2022 Microsoft Corporation Developer Edition (64-bit) on Linux (Ubuntu 22.04.5 LTS) <X64> .... .... Detected 12792 MB of RAM, 12313 MB of available memory, 12313 MB of available page file. This is an informational message; no user action is required” - This was despite the container being configured with a 3Gi memory limit: kubectl get pod mssql-0 -n cgrouptest -o jsonpath="{.status.qosClass}`n{.spec.containers[*].resources.limits.memory}" Guaranteed 3Gi Even though users limited the memory for SQL Server containers to 3 GB, SQL Server was still able to see the entire physical memory on the host and tried using that ending up in OOM crashes. But, With the release of SQL Server 2025 preview and SQL Server 2022 CU 20, the memory limits are now correctly enforced. Here's what the error log looks like with cgroup v2 support: “Microsoft SQL Server 2022 (RTM-CU20) (KB5059390) - 16.0.4205.1 (X64) Jun 13 2025 13:38:45 Copyright (C) 2022 Microsoft Corporation Developer Edition (64-bit) on Linux (Ubuntu 22.04.5 LTS) <X64> .. .. Detected 2458 MB of RAM, 1932 MB of available memory, 1932 MB of available page file. This is an informational message; no user action is required” The limits are same as previous case with memory limited to 3 GB as shown below, SQL Server ends up with 80% of 3 GB as the limit that is 2458 MB as printed in the errorlog. Below is the container configuration with a 3Gi memory limit: kubectl get pod mssql-latest-0 -n cgrouptest -o jsonpath="{.status.qosClass}`n{.spec.containers[*].resources.limits.memory}" Guaranteed 3Gi Learn More SQL Server on Linux Overview SQL Server 2025 Release Notes Deploy a SQL Server Linux container to kubernetes Deploy SQL Server on OpenShift or Kubernetes Understanding Cgroup v2on Kubernetes Understanding Cgroups on RHEL Wrapping Up With the introduction of cgroup v2 support in SQL Server 2025 and SQL Server 2022 CU 20, Linux-based deployments gain a powerful tool for smarter resource management. Whether you're running SQL Server in containers or on bare metal, cgroup v2’s unified hierarchy, simplified configuration, and real-time pressure metrics offer a more predictable and efficient way to enforce Quality of Service. From isolating workloads in Kubernetes to dynamically tuning performance under contention, this enhancement empowers DBAs and platform engineers to deliver consistent service levels across diverse environments. As SQL Server continues to evolve on Linux, embracing cgroup v2 is a strategic step toward building resilient, high-performance data platforms. Thanks, Engineering: Andrew Carter (Lead), Nicolas Blais-Miko Product Manager: Attinder Pal Singh and Amit Khandelwal
Managed Identity support for Azure Key Vault in SQL Server running on Linux
We are happy to announce that, you can now use Managed Identity to authenticate to Azure Key Vault from SQL Server running on Azure VM (Linux) available from SQL Server 2022 CU18 onwards. This blog will walk you through the process of using a user-assigned managed identity to access Azure Key Vault and configure Transparent Data Encryption(TDE) for a SQL database. Managed Identity: Microsoft Entra ID, formerly Azure Active Directory, provides an automatically managed identity to authenticate to any Azure service that supports Microsoft Entra authentication, such as Azure Key Vault, without exposing credentials in the code. Refer Managed identities for Azure resources - Managed identities for Azure resources | Microsoft Learn for more details. VM Setup and Prerequisites: Before diving into the setup, it's essential to ensure that your Azure Linux VM has SQL Server installed and that the VM has identities assigned with the necessary key vault permissions. Set up SQL Server running on Azure Linux VM. Refer SQL Server on RHEL VM in Azure: RHEL: Install SQL Server on Linux - SQL Server | Microsoft Learn, SQL Server on SLES VM in Azure: SUSE: Install SQL Server on Linux - SQL Server | Microsoft Learn, SQL Server on Ubuntu VM in Azure: Ubuntu: Install SQL Server on Linux - SQL Server | Microsoft Learn for more details. Create user-assigned Managed Identity. Refer https://learn.microsoft.com/en-us/azure/active-directory/managed-identities-azure-resources/how-to-manage-ua-identity-portal for more details. Go to Azure Linux VM resource in the Azure portal and click on Identity tab under security blade. Go to the User assigned tab in the right side panel and click on Add. Select the user-assigned managed identity and click on Add. Create a Key Vault and Keys. Refer Integrate Key Vault with SQL Server on Windows VMs in Azure (Resource Manager) - SQL Server on Azure VMs | Microsoft Learn for more details. Assign Key Vault Crypto Service Encryption User role to the user-assigned managed identity to perform wrap and unwrap operations. Go to the key vault resource that you created, and select the Access control (IAM)setting. Select Add> Add role assignment. Search for Key Vault Crypto Service Encryption User and select the role. Select Next. In the Members tab, select Managed identity option and click on Select members option, and then search for the user-assigned managed identity that you created in Step 3. Select the managed identity and then click on Select button. Setting the primary identity on Azure Linux VM To set the managed identity as the primary identity for Azure Linux VM, you can use the mssql-conf tool packaged with SQL Server. Here are the steps: Use the mssql-conf tool to manually set the primary identity. Run the following commands: sudo /opt/mssql/bin/mssql-conf set network.aadmsiclientid <client id of the managed identity> sudo /opt/mssql/bin/mssql-conf set network.aadprimarytenant <tenant id> 3. Restart the SQL Server: sudo systemctl restart mssql-server Enable TDE using EKM and managed identity: Refer Managed Identity Support for Extensible Key Management (EKM) with Azure Key Vault (AKV) - SQL Server on Azure VMs | Microsoft Learn for configuration steps for Azure Windows VM. These steps remain same for SQL Server running on an Azure Linux VM. 1.Enable EKM in SQL Server running on the Azure VM. 2.Create credential and encrypt the database. When using the CREATE CREDENTIAL command in this context, you only need to provide the 'Managed Identity' in the IDENTITY argument. Unlike earlier scenarios, you do not need to include a SECRET argument. This simplifies the process and enhances security by not requiring a secret to be passed. Conclusion: Using managed identity to access Azure Key Vault in SQL Server running on an Azure Linux VM boosts security, streamlines key management, and supports compliance. With data protection being paramount, Azure Key Vault’s integration along with managed identity offers a robust solution. Stay tuned for more insights on SQL Server on Linux! Official Documentation: Managed Identity Support for Extensible Key Management (EKM) with Azure Key Vault (AKV) - SQL Server on Azure VMs | Microsoft Learn Extensible Key Management using Azure Key Vault - SQL Server Setup Steps for Extensible Key Management Using the Azure Key Vault Azure Key Vault Integration for SQL Server on Azure VMs
