Learn more about FabCon and SQLCon 2026
The excitement surrounding this event reflects the same momentum we’re seeing across our data portfolio. Just two and a half years after Microsoft Fabric reached general availability, it’s already serving more than 31,000 customers and remains the fastest-growing data platform in Microsoft’s history. Fortune 500 companies like The Coca-Cola Company are already using Fabric at scale across their organizations.

Microsoft Fabric is helping us evolve our data foundation into a more unified, AI-ready platform. Combined with Power BI and capabilities like Fabric IQ, it enables the enterprise to turn data into intelligence and act on it faster.

Shekhar Gowda, Vice President of Global Marketing Technologies at The Coca-Cola Company
Our databases are accelerating just as quickly, with SQL Server 2025 growing more than twice as fast as the previous version.

Today, we’re thrilled to share how we are bringing the power of databases and Fabric together to form a truly converged data platform—one that unifies transactional, operational, and analytical data under a single, consistent architecture. I’ll also highlight how we’ve enhanced Fabric to help you transform data into the semantic knowledge AI needs to understand your business, powered by Fabric IQ and Power BI’s industry-leading semantic model technology.

Introducing the Database Hub in Microsoft Fabric
Databases sit at the heart of the enterprise data estate—a system of record powering applications, transactions, and mission‑critical insights. Yet as organizations scale across cloud, on‑premises, and edge environments, database estates have become increasingly fragmented and isolated. As AI places even greater demands on data estates, unifying databases under a single access point and control plane has become essential.

To address this challenge, Fabric is expanding its role as the central access point for enterprise data with the Database Hub in Fabric, now available in early access. Database Hub in Fabric provides a unified database management experience that brings together databases across edge, cloud, and Fabric into a single, coherent view. Teams now have one place to explore, observe, govern, and optimize their entire database estate—including Azure SQL, Azure Cosmos DB, Azure Database for PostgreSQL, SQL Server (enabled by Azure Arc), Azure Database for MySQL, and Fabric Databases—without changing how each service is deployed.

Built for scale, the Database Hub in Fabric introduces an agent‑assisted, human-in-the loop approach to database management. With built-in observability, delegated governance, and Microsoft Copilot-powered insights, teams can deploy intelligent agents to continuously reason over estate‑wide signals and surface what changed, explain why it matters, and guide teams toward what to do next. The result is a simpler, more confident way to manage databases at scale. Over time, this model enables database estates to become more proactive, resilient, and intelligent, laying the foundation for greater autonomy, while keeping humans firmly in control of goals, boundaries, and trust.

Learn more about Database Hub in Fabric and what’s new across Databases
Bringing databases together under a single management layer is a critical step as you prepare your estates for AI at scale. But it’s not the end of the journey. The challenge shifts from where data lives to how data is understood, connected, and activated across the enterprise.

Getting your data estate ready for AI with Fabric
As organizations move from traditional applications to AI‑powered, multi‑agent systems, the advantage is shifting away from the specific model you deploy. It now lies in the intelligence and context that allow agents to understand how your business is run, the state of your business, and your institutional knowledge to help take meaningful action.

This is the challenge Microsoft IQ is designed to address. Unlike point solutions on the market today, Microsoft IQ provides an intelligence layer that delivers shared, enterprise-grade business context to every agent. That context is built from three complementary sources: productivity signals from Work IQ, institutional knowledge from Foundry IQ, and live business data from Fabric IQ.

However, like the database layer, while the IQ context layer is a critical part of a successful, and healthy AI foundation, it is not the full story. Building a complete AI-ready data foundation requires investing in four core steps:

Unifying your data estate to eliminate silos and reduce architectural complexity.
Processing and harmonizing data so it becomes AI-ready, clean, connected, and structured for both operational and analytical use.
Curating semantic meaning to give agents contextual understanding, enabling them to interpret data the way your teams already do. This is where Microsoft IQ comes into play.
Empowering AI agents to act, applying that context to automate workflows, accelerate decisions, and transform operations end‑to‑end.
Unifying your data estate with Microsoft OneLake
Every AI initiative starts with the same fundamental challenge: understanding where your data lives and how to bring it together. Microsoft OneLake was built to solve that problem by unifying data across clouds, on-premises environments, and third-party platforms into a single logical data lake without unnecessary extracting, transforming, and loading (ETL), fragmentation, or duplicated copies.

Are my agents hunting for data?

Watch the podcast
Connecting to more sources than ever before
Today, we’re expanding Mirroring in Fabric to support even more systems our customers rely on. Mirroring for SharePoint lists and Dremio are now in preview with Azure Monitor coming soon, while mirroring for Oracle and SAP Datasphere are generally available—all of which are available as part of the core mirroring capabilities. We are also introducing extended capabilities in mirroring designed to help you operationalize mirrored sources at scale, including Change Data Feed (CDF) and the ability to create views on top of mirrored data, starting with Snowflake. Extended capabilities for mirroring will be offered as a paid option.

Shortcut transformations are also now generally available, allowing data to be shaped automatically as it connects to or moves within OneLake. You can convert formats such as Excel to Delta tables, now in preview, and apply AI-powered transformations.

Additionally, we are continuing to invest in open interoperability, ensuring OneLake works seamlessly with the platforms organizations already use. We are excited to announce the ability to natively read from OneLake through Azure Databricks Unity Catalog is now in public preview. We also recently announced the general availability of our interoperability with Snowflake.

I’m also excited to share that Auger, a rapidly growing supply chain platform designed to bring intelligence and automation to global operations, has built its platform on Fabric, with all data stored natively in OneLake. This architecture enables Auger customers to seamlessly access their operations data through OneLake shortcuts within their own Fabric environments and use the full power of the platform including Power BI, Fabric data agents, and more. Learn more in my blog, co-authored with Auger Chief Executive Officer Dave Clark.

Protect your data with OneLake security, now generally available
Security and governance remain foundational to OneLake. I’m thrilled to announce OneLake security will be generally available in the coming weeks, enabling data owners to define roles, enforce row- and column-level controls, and manage permissions through a single unified model that follows the data.

To learn more about these announcements, read the OneLake blog and the Fabric Data Factory blog.

Processing and harmonizing data with Fabric analytics
AI agents are only as reliable as the data you feed them. Before data can train or ground an agent, it must be integrated, cleaned, and structured, so the agent operates from consistent, trusted information. With industry-leading engines in Fabric like Spark, T-SQL, KQL, and Analysis Services, we can equip data teams to do exactly that.

Now, we are expanding these capabilities with the introduction of Runtime 2.0 in preview, purpose-built for large-scale data computation. It incorporates Apache Spark 4.x, Delta Lake 4.x, Scala 2.13, and Azure Linux Mariner 3.0 to power advanced enterprise workloads. Materialized lake views are also now generally available, simplifying medallion architecture implementation in Spark SQL and PySpark and enabling always up-to-date pipelines with no manual orchestration. In addition, a new agentic Copilot experience in notebooks delivers deeper context awareness, reasoning over your workspace, and generating code with greater speed and precision.

For real-time scenarios, we’re launching Microsoft Fabric Maps into general availability. Maps add geospatial context to your agents and operations by turning large volumes of location-based data into interactive, real-time visual insights.

For a comprehensive overview of these announcements and much more, read the Fabric Analytics announcement blog and the Fabric Real-Time Intelligence announcement blog.

Creating semantic meaning with Fabric IQ
Preparing raw data for AI is essential. The next step is transforming that data into meaningful, unified business context. That is where Fabric IQ comes in.

Fabric IQ unifies analytical data and operational data, including telemetry, time series, graph, and geospatial data, within a shared semantic framework of business entities, relationships, properties, rules, and actions. Instead of thinking in terms of tables and schemas, your teams and agents can operate on this framework, or ontology, aligned to how the business actually runs.

Fabric IQ ontologies will soon become accessible through an MCP server in preview, enabling agents to discover, understand, and act on this semantic layer. Ontologies can also serve as context sources for maps and soon in operations agents in Fabric, extending shared business context directly into operational decision-making and execution.

We are also excited to announce planning in Fabric IQ, a new enterprise planning capability that enables organizations to create plans, budgets, forecasts, and scenario models directly on top of Fabric’s semantic models. By complementing Fabric IQ’s ontologies with integrated planning, you get a complete, contextual view of your historical, real-time, and forward planning data. This allows users and agents to quickly answer what has happened, what is happening, and what should happen all from a single source. See this in action:

Finally, we recently announced a strategic partnership with NVIDIA to power the next generation of Physical AI by integrating Real-Time Intelligence and Fabric IQ with NVIDIA Omniverse libraries. The combined platform unifies real‑time operational data, business semantics, and physical simulation to enable organizations to optimize their physical operations in scenarios like intelligent digital twins, predictive maintenance, autonomous logistics, and energy optimization.

To learn more about all of our partner announcements, read the Fabric ISV announcement blog and the planning in Fabric IQ blog.

Enhancing the underlying Fabric IQ technology
Powering much of Fabric IQ’s rich experience is a combination of Power BI’s industry-leading, rich semantic model technology and graph in Fabric, our highly scalable graph database. Already delivering insights to more than 35 million active users, semantic models provide the ideal foundation for training agents through Fabric IQ. Now, with the general availability of Direct Lake on OneLake, your tables can be read directly from OneLake with native security enforcement, richer cross-item modeling, and import-class performance without data movement or refresh.

I’m also excited to share that graph in Fabric will be generally available in the coming weeks, enabling teams to visualize and query complex relationships across customers, partners, and supply chains.

To learn more, check out the Fabric IQ announcement blog and the Power BI announcement blog.

Empowering agents to act with Fabric data and operations agents
Frontier organizations are moving beyond general-purpose assistants and instead, adopting multi-agent systems composed of specialized agents. These agents are each grounded on specific data and reusable across different systems, allowing you to deliver more accurate, accelerated, and scalable outcomes.

To support your multi-agent systems, Fabric comes with built-in agent creation capabilities with Fabric data agents and operations agents. I’m excited to share that Fabric data agents are now generally available. Fabric data agents can be thought of as virtual analysts, aligned to specific domain data to support deeper analysis and deliver insights. Operations agents complement them by monitoring real-time data, detecting patterns, and taking proactive action.

Check out a quick demo of operations agents in Fabric:

These agents can be used across Fabric or as foundational knowledge sources in leading AI tools like Microsoft Foundry, Copilot Studio or even Microsoft 365 Copilot. To learn more about our AI announcements, check out the Fabric analytics blog covering data agents and the Fabric IQ blog covering operations agents.

Building mission-critical applications with developer experiences in Fabric
Developers building the next generation of AI applications need a comprehensive, cost-effective data platform that’s already integrated with your existing tools and workflows. Today, we are expanding Fabric’s developer tooling to meet that demand.

First, Fabric Model Context Protocol (MCP) is advancing with two major milestones. Fabric local MCP is now generally available, providing an open-source local server that connects AI coding assistants such as GitHub Copilot directly to Fabric. Alongside this, we’re introducing the public preview of Fabric remote MCP, a secure, cloud‑hosted execution engine that enables AI agents and automation tools to perform authenticated actions in Fabric.

We’re also enhancing our Git integration with selective branching, allowing developers to branch out for a specific feature and pull only the items they need. You also get improved change comparisons to more easily review recent updates, and new folder relationships which show how feature workspaces connect to source workspaces.

We’re also launching two open-source projects to help teams move faster with Fabric: Agent Skills for Fabric and Fabric Jumpstart. Agent Skills for Fabric is an open-source set of purpose-built plugins that let you use natural language in the GitHub Copilot terminal to harness the full power of Microsoft Fabric. Additionally, Fabric Jumpstart is designed to help you get off the ground with detailed guidance, reference architectures, and single‑click deployments for sample datasets, notebooks, pipelines, and reports.

Finally, we are announcing that the Fabric Extensibility Toolkit (FET), an evolution of the Workload Development Kit (WDK), is now generally available. Along with this release, we are enabling support for full CI/CD, variable library, and a new management experience in the Admin portal.

Read the Fabric Platform announcement blog
Migrating your existing Azure service to Fabric
As Fabric continues to grow in functionality, we are also simplifying the migration from other Azure services. In addition to our existing Synapse tooling, we are bringing new migration assistants for Azure Data Factory, Azure Synapse Analytics, and Azure SQL in public preview.

The new Fabric migration assistant for Azure Data Factory and Synapse Analytics helps move your existing pipelines and artifacts like Spark pools and notebooks into Fabric with minimal disruption. It’s designed to support incremental modernization, allowing teams to evaluate, convert, and optimize pipelines as they transition to Fabric. The migration assistant for SQL databases helps move SQL Server into Fabric by importing schemas through DACPACs, identifying and resolving compatibility issues with AI assistance, and guiding teams through assessment and data copy workflows for a smoother cutover.

See more Fabric innovation
Explore the AI shift with The Shift podcast
In addition to the announcements above, we are also rolling out a broad set of Fabric innovations across the platform. For a deeper look at the updates and what’s new this month, visit the Fabric March 2026 Feature summary blog, the Power BI March 2026 feature summary blog, and the latest posts on the Fabric Updates channel.

Explore additional resources for Microsoft Fabric
Sign up for the Fabric free trial. View the updated Fabric Roadmap. Try the Microsoft Fabric SKU Estimator.
Visit the Fabric website. Join the Fabric community. Read other in-depth, technical blogs on the Microsoft Fabric Updates Blog.
Read additional blogs by industry-leading partners
Sonata Software: Building an AI-ready data platform with data agents, ontology, and governance in Microsoft Fabric
Quadrant Technologies LLC: Real-Time Operational Intelligence in Microsoft Fabric: Deep Dive into RTI Capabilities, Anomaly Detection and Activator Alerting
Inspark: Why switch from Azure Synapse to Microsoft Fabric?
Esri: Unlock the power of location intelligence with ArcGIS for Microsoft Fabric
Dream IT Consulting Services: 8 Real-World Use Cases of Data Agents in Microsoft Fabric
UB Technology Innovations Inc.: From Data Platform to Decision Platform: How Microsoft Fabric and Copilot are Redefining Enterprise Analytics
Simpson Associates: Fabric Data Warehouse: Bringing Structure to Modern Data Strategies
Synapx Ltd.: Migrating Power BI to Microsoft Fabric Lakehouse with Medallion Architecture: A Strategic Imperative for Modern Construction Enterprises
Cloud Services: Real-Time Intelligence in Action: How Microsoft Fabric Helped Delfi Transform Its Newsroom
Cloud Services: Microsoft Fabric Data Agents: A New Reality
iLink Digital: Detect to Act in Seconds: How Real-Time Intelligence Is Rewriting the Rules of Emissions Management
Valorem Reply: How Nonprofits Are Rethinking Data with Microsoft Fabric

The post FabCon and SQLCon 2026: Unifying databases and Fabric on a single data platform appeared first on Microsoft SQL Server Blog.

One consistent SQL is a promise of a unified experience that spans edge, cloud, and software as a service (SaaS), empowering developers to create intelligent applications with ease, while enabling data professionals to modernize on their terms. Write once, deploy anywhere because customers run diverse SQL estates, and we meet them wherever they are. Whether you’re running workloads with SQL Server, modernizing in Azure SQL, or activating real-time analytics in Microsoft Fabric, one consistent SQL unifies your data estate, bringing platform consistency, performance at scale, advanced security, and AI-ready tools together in one seamless experience and creates one home for your SQL workloads in the era of AI.

With a consistent platform, optimized performance, and multi-layered security, workloads scale dynamically while staying secure and highly available. And building intelligent, scalable applications is faster than ever with developer-first tools combined with AI capabilities. This is enterprise-grade performance for the era of AI, with one consistent SQL powering innovation across hybrid, multi-cloud, and AI-powered environments, all anchored by a unified data estate.

Delivering a consistent SQL platform across cloud and on-premises

From edge to cloud, one consistent SQL is Microsoft’s commitment to deliver a consistent experience—powering mission-critical workloads, next-generation apps, and data-driven intelligence. It provides unified management across infrastructure, platform, and software services for consistent operations in hybrid scenarios. Developers can use familiar SQL skills and tools to build and manage applications across environments, while sovereign cloud support addresses data residency and compliance requirements for regulated industries.

And now, the centerpiece of this vision takes the stage: SQL Server 2025 is now generally available. Built on SQL Server’s foundation of security, performance, and availability, this release introduces built-in AI capabilities and developer-focused enhancements. These features enable organizations to use existing data to support AI initiatives securely and at scale, all within SQL Server using the T SQL language.

Achieving optimized SQL performance and advanced security

In a world where trust is non-negotiable, organizations expect the same performance, availability, and security standards everywhere in their data lives. They adapt to the demands of your workload without compromise—delivering resilience and speed while keeping data secure and operations steady. These expectations are heightened for mission-critical workloads, where uptime and reliability directly impact return on investment. Businesses need a platform that not only meets these requirements but also evolves to handle growing complexity without adding operational burden.

The next generation of Azure SQL Managed Instance is now generally available to help organizations modernize with improved performance and simplified migration. The release offers expanded storage and database capacity, flexible compute and memory options, and features designed to support diverse workload requirements. These enhancements provide a foundation for scaling applications and managing data securely while maintaining compatibility with existing SQL investments. Customers are already benefiting from Azure SQL Managed Instance. Hexure, a life insurance software company, slashed processing time by 97.2%.

The path to Azure SQL Managed Instance also got easier. SQL Server migration in Azure Arc is now generally available. Copilot-assisted migration streamlines the entire process with real-time replication, confident cutover, and trusted failover—reducing months of work to days and lowering total cost of ownership.

Knowing that we have a reliable and highly secure database platform positions us to think about how we can use AI in ways that will benefit our customers and their customers most. With Azure SQL Managed Instance in place, we’re very well equipped to continue in our role as a leader in insurance tech

—Warren Perlman, CTO, Hexure

Empowering developers with AI-ready SQL tools at scale

One consistent SQL means you can use your existing skills and familiar development tools together with AI-powered capabilities to simplify application creation. As organizations look to integrate generative AI into business processes, complexity and time to value remain major challenges. Analysts predict that most AI applications will be built on existing data platforms—reducing development effort and accelerating delivery. Customers want integration, not disruption, and they expect AI assistance embedded in the tools they already use.

This vision is supported by features that combine intelligence with security. GitHub Copilot integration enables developers to work with AI assistance directly in environments like Visual Studio Code and SQL Server Management Studio 22. Native support for retrieval of augmented generation scenarios includes vector search and semantic indexing within SQL Server and Azure SQL, while secure enclaves and Always Encrypted protect sensitive data during processing. Connections to Azure AI services and governance tools streamline data preparation and compliance, while elastic infrastructure supports training, inference, and deployment at scale. 

Creating a unified data estate for analytics and AI

Microsoft Fabric connects operations, analytics, and governance in one unified experience, unlocking the full potential of SQL data. As organizations prepare for real-time AI applications, the ability to bridge transactional and analytical workloads becomes essential. Analysts describe this capability as “translytical,” a foundation for responsive applications that combine speed with depth. A future-ready data strategy must integrate operational data with analytical insight, and Fabric delivers that integration without adding complexity.aka

Today at Microsoft Ignite 2025, we announced two key advancements: the general availability of Fabric databases and database Mirroring in Fabric. Fabric databases unify operational and analytical data within Fabric, backed by OneLake, the open data foundation for analytics and AI. SQL database in Fabric supports transactional processing, real-time analytics with zero Extract, Transform, and Load (ETL), and AI workloads side-by-side. In addition, database Mirroring enables replication of SQL Server and Azure SQL into Fabric for analytics and AI scenarios without migration or refactoring. Early adopters such as AP Pension have consolidated decades of fragmented data using Mirroring for SQL Server in Fabric and SQL database in Fabric, creating a centralized architecture with automated delivery and strong governance. These capabilities position Fabric as a cornerstone for organizations seeking to modernize data strategies and prepare for AI-powered applications.

Eastman built a new agentic sales copilot app, enabling their sellers to instantly query unified customer data using natural language. By integrating SQL querying with Fabric’s analytics and vector capabilities, the copilot retrieves hyper-precise answers directly from the database.

When it comes to SQL in Fabric, a huge advantage is you have the robustness of SQL Server, but already in the context of Fabric. The fact that it already has so many security features and integrations with the rest of the Fabric platform is a huge advantage.

—Logan Finke, Principal AI Data Architect at Eastman

Innovate with one consistent SQL

One SQL is a promise of consistency, security, and flexibility from edge to cloud, helping you innovate without disruption. Build intelligent apps powered by agentic AI, unlock real-time insights, and meet compliance demands, all with the tools and skills you already trust. Make your legacy databases your launchpad to innovation.

One engine. One experience. One SQL.

Take the next step today

• Learn more about SQL Server 2025 and download now.
• Learn more about next-generation Azure SQL Managed Instance.
• Learn more about SQL database in Fabric and database Mirroring in Fabric.

The post One consistent SQL: The launchpad from legacy to innovation appeared first on Microsoft SQL Server Blog.

End-to-end migration simplified

If you’ve been using SQL Server enabled by Azure Arc, you’re likely familiar with continuous migration assessments that offer target recommendations, technical readiness, and cost estimates. Now, we’re taking the next step forward by introducing automated, end-to-end migration capabilities in SQL Server enabled by Azure Arc.

Once you’ve assessed the Azure readiness of your SQL Server instances, you can now select or provision your Azure targets such as Azure SQL Managed Instance, without jumping between various tools or places in the Azure portal. This streamlined workflow eliminates context switching and simplifies provisioning. You’ll see estimated costs during the provisioning process, giving you clear visibility and confidence to plan ahead. Plus, you can take advantage of the free Azure SQL Managed Instance offer to evaluate at no cost, making it easier to get started. 

Real-time database replication is also integrated into the new migration capability. This new method, built on top of distributed availability groups, enables near real-time database replication from SQL Server to Azure SQL Managed Instance. Setting up real-time replication manually can be a complex multi-step process, but Azure Arc simplifies the entire process while providing best-in-class monitoring. If a customer decides to go back to on-premises, Azure SQL Managed Instance Link also supports seamless failback (if the source SQL Server instance is SQL Server 2022 and above). 

Migrate with confidence 

The new capability empowers customers to migrate with confidence. Before officially cutting over, you can validate that the target Azure SQL Managed Instance meets your business requirements by using the target instance as a read-only replica.  

In addition, the client connection summary feature in SQL Server, enabled by Azure Arc, automatically and continuously captures and displays which clients are connecting to each instance. This replaces the previous manual and time-consuming process of tracing applications to their databases, giving customers clear visibility and helping ensure a smooth transition to Azure.

Get started today 

If you’re looking to simplify and accelerate your migration to Azure, this new connected capability can help you get there faster—with less downtime, lower overhead, and more confidence. 

• Learn more on our Tech Community blog.
• Learn more about the new migration capability in Azure Arc on Microsoft Learn.
• Onboard your SQL Server to Azure Arc today.
• Learn more about continuous migration assessment from SQL Server enabled by Azure Arc.

Frequently asked questions 

1. What is SQL Server enabled by Azure Arc?  

SQL Server enabled by Azure Arc extends Azure services to SQL Server instances hosted outside of Azure: in your data center, in edge site locations like retail stores, or any public cloud or hosting provider. 

Azure Arc enables you to consistently manage SQL Server instances across hybrid and multicloud environments, bringing cloud innovations such as automated updates, unified policy, best practices assessment, and advanced security to SQL Server running anywhere.

2. What’s the continuous migration assessment from Azure Arc?  

Microsoft has announced the general availability of continuous migration assessments for SQL Server enabled by Azure Arc, marking a step forward in simplifying cloud migration planning. This release introduces a redesigned assessment experience that provides deeper insights and more intuitive navigation, especially for single Arc-enabled instances. 

One of the standout features is the integration of retail pricing visibility across all Azure savings options, including Azure Hybrid Benefit (AHB), reserved instances, and Azure savings plans. These pricing insights are now available for Azure SQL Database, SQL Managed Instance, and SQL Server on Azure Virtual Machines (VMs), helping users make informed cost decisions.  

3. What is Azure Database Migration Service? 

Azure Database Migration Service is a fully managed service designed to seamlessly migrate databases to Azure with minimal downtime. It supports both homogeneous migrations (such as SQL Server to Azure SQL) and heterogeneous migrations (such as Oracle to Azure PostgreSQL).

4. What are the migration methods in the new migration capability? 

The following methods are built into the migration process. Azure SQL Managed Instance link enables near real-time database replication using distributed availability groups. Log Replay Service uses SQL Server log-shipping technology and requires a brief planned cutover. Review the Microsoft Learn page to understand the differences between these two migration methods and choose the option that best suits your needs.

The post Accelerate SQL Server Migration to Azure with Azure Arc  appeared first on Microsoft SQL Server Blog.

SQL Server 2025, now in public preview, empowers customers to develop modern AI applications securely using their data, complete with best-in-class security, performance, and availability. It provides built-in, extensible AI capabilities, enhanced developer productivity, and seamless integration with Microsoft Azure and Microsoft Fabric—all within the SQL Server engine using familiar T-SQL language. 

Your data, any model, anywhere 

One of the most exciting new capabilities of SQL Server 2025 is the integration of AI directly into the database engine, enabling more intelligent search. With built-in vector search capabilities, you can perform semantic searches over your own data to find matches based on similarity, alongside full text search and filtering you are already using in SQL Server. This built-in capability opens up a host of exciting new use cases such as discovering deeper connections within large datasets, providing a natural conversational experience across various enterprise systems.  

SQL Server 2025 introduces enhanced model management by building model definitions directly into T-SQL, enabling seamless integration with popular AI services such as Azure AI Foundry, Azure OpenAI Service, OpenAI, Ollama, and others. Models are all accessed through REST APIs allowing you to deploy any model securely isolated from the SQL Server engine, anywhere from ground to cloud. As developers test embedding models to find the best fit for their use cases, whether running open-source models on laptops or hosting purpose-trained models, SQL Server 2025 makes it convenient to switch models without needing to change the code. 

This release also provides other essential building blocks for AI development and operational retrieval-augmented generation (RAG) patterns powered by AI agents. It includes vector embedding generation and text chunking built into T-SQL, using Disk Approximate Nearest Neighbor (DiskANN) as a vector index for faster, resource-efficient, and accurate results. Additionally, SQL Server 2025 offers seamless integration with popular AI frameworks like LangChain, Semantic Kernel, and Entity Framework Core. 

“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, we deliver a seamless, natural conversational experience across enterprise environments.”

—Markus Angenendt, Data Platform Infrastructure Lead, Kramer & Crew  

Microsoft’s most significant release for SQL developers in the last decade 

We understand that developers need the right tools and interfaces for modern, data-intensive applications. SQL Server 2025 delivers a rich set of feature enhancements that significantly streamline development process, reduce code complexity, and improve developer productivity. Along with built-in AI capabilities, this release makes SQL Server 2025 the most significant release for SQL developers since the introduction of SQL Server 2016 a decade ago.  

Enhancing data enrichment is our first area of focus in this release. SQL Server 2025 offers native JSON support, empowering developers to process JSON documents natively. Combined with REST APIs and Regular Expressions (RegEx) enablement, developers can now enrich, validate, and manipulate their datasets with external data sources. This allows for building more dynamic, enterprise-grade applications with richer functionality and enhanced performance. 

Empowering developers to build real-time, event-driven applications with SQL Server is another scenario that this release unlocks. Change Event Streaming allows users to consume transaction log changes as events directly from SQL Server to Microsoft Azure Event Hubs. This provides a new method to mitigate some of the issues developers have seen with the Input/Output (I/O) overhead of Change Data Capture (CDC). It also opens new possibilities such as developing real-time, event-driven applications powered by AI agents. 

There’s also excitement on the language and tooling front. We’re thrilled to announce the preview of our new open-source Python driver for SQL Server.¹ Built from the ground up, this driver offers Python developers a robust, efficient, and fully open-source solution for connecting to SQL Server, as simple as pip install. In addition, we are bringing AI-powered assistance directly into your workflow with the integration of MSSQL Extension for Visual Studio Code with GitHub Copilot, now in preview. With GitHub Copilot aware of your SQL Server database connection, developers can generate SQL and object-relational mapping (ORM) migrations, explore schemas, optimize queries with intelligent suggestions, and streamline database interactions—all within in Visual Studio Code.  

“I am genuinely enthusiastic about the AI advancements in SQL Server 2025. These features, along with the enhancements in RegEx and JSON data support, promise to make AI functionalities accessible to a broader range of software applications, and significantly enhance our database operations.” 

—Jacob Saugmann, SQL Specialist, J.H. Schultz Information A/S

Best-in-class security, performance, and availability 

This release builds on SQL Server’s history as an industry leader in database security, performance, and availability. For our enterprise customers, security is non-negotiable. SQL Server remains as the most secure database in the last decade.² SQL Server 2025 continues the product’s legacy of top-notch security by incorporating modern identity and encryption practices. Support for Microsoft Entra managed identities improves credential management and reduces potential vulnerabilities.³

We’re bringing Optimized Locking to SQL Server, to reduce lock memory consumption and minimize blocking for concurrent transactions through Transaction ID (TID) Locking and Lock After Qualification (LAQ). This capability enables customers to increase uptime and enhance concurrency and scale for SQL Server applications. 

SQL Server 2025 has over 50 enhancements made to the database engine including key improvements for HADR all based on customer feedback. This new release will bring enhancements to performance for applications with no code changes required through Intelligent Query Processing (IQP) and columnstore improvements, enhancements for query processing, and enabling Query Store for readable secondaries.  

“Security Cache Improvement proved invaluable for high-demand environments like ours, reducing disruption when applying permissions on servers with 20,000–25,000 active connections. This enhancement ensures minimal performance impact, streamlining security management. The ordered non-clustered Columnstore index significantly improved query performance by over 63%, optimizing workloads reliant on analytical processing.”

—Madhab Paudel, Database Engineer, Entain

Cloud agility through Azure 

To build scalable analytics, data needs to be extracted, transformed, normalized, and made available in a central place. SQL Server 2025 will support database mirroring in Fabric, giving you near real-time analytics using a zero extract, transform, and load (ETL) experience and allowing you to offload your analytical workloads to Fabric.³  

Azure is a critical component of SQL Server. With Azure Arc, SQL Server 2025 will continue to offer cloud capabilities to enable customers to better manage, secure and govern your SQL estate at scale across on-premises and cloud. 

“Fabric mirroring for SQL Server 2025 helps MSC to build the bridge to bring our operational data into Microsoft Fabric.”

—Javier Villegas, IT Director of DBA and BI Services, Mediterranean Shipping Company

Get started with SQL Server 2025 today

With every AI-powered query for hybrid search, every millisecond saved in query execution, every change event streamed in real time, SQL Server 2025 is a critical building block for modern data-intensive applications in this AI era. Ready to try it out? Learn more about SQL Server 2025.

SQL Server Management Studio (SSMS) 21, now generally available, is based on Visual Studio 2022 and includes 64-bit support. This modernized version is available from the Visual Studio Installer, offers automatic updates, and introduces Git integration, query editor enhancements, and a new connection experience.

Microsoft Copilot in SSMS, now in preview, is available as an optional workload when installing SSMS 21, and assists customers in writing, editing, and fixing T-SQL queries using natural language. Leveraging database context, it also helps with database administration, maintenance, configuration and more.³

Explore solutions and capabilities

• Learn more from our Microsoft Build 2025 session: SQL Server 2025: The Database Developer Reimagined.
• Deep-dive blog on Tech Community.
• Explore solutions from Microsoft SQL Server.
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SQL Server 2025

Explore new capabilities in AI development, enhanced model management, and more

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¹ Public preview of Python driver is June 1, 2025. The alpha version is available on GitHub today. 

² According to the National Institute of Standards and Technology Comprehensive Vulnerability Database, as of December 2024.

³ Although SQL Server 2025 in public preview is free to try, using some features such as Microsoft Entra, Fabric and Copilot in SQL Server Management Studio 21 could incur costs based on usage. Try Azure for free and explore Fabric trial capacity.

The post Announcing SQL Server 2025 (preview): The AI-ready enterprise database from ground to cloud appeared first on Microsoft SQL Server Blog.

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.

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: http://approjects.co.za/?big=en-us/sql-server
• MSSQL Extension for Visual Studio Code with GitHub Copilot:  https://aka.ms/vscode-mssql-copilot

The post SQL Server 2025 – AI ready enterprise database from ground to cloud appeared first on Microsoft SQL Server Blog.

Mirroring provides a modern way of accessing and ingesting data continuously and seamlessly from any database or data warehouse into OneLake in Microsoft Fabric. This is all in near real-time thus giving users immediate access to changes in the source!

Today we are thrilled to announce that Mirroring for SQL Server in Fabric for all in-market versions of SQL Server from SQL Server 2016 to SQL Server 2022 is in preview.

Additionally, with the preview announcement of SQL Server 2025, we are also excited to announce the preview of Mirroring for SQL Server 2025 in Fabric.

Let’s take a look at the capabilities for each of these previews.

Mirroring in Fabric from any of your SQL Server sources ensures that your source transactional SQL Server database is always up to date and available in the Fabric OneLake, providing a solid foundation for reporting, advanced analytics, AI, and data science. There is no complex setup or ETL for Mirroring. You setup the mirror from Fabric Portal by providing the SQL Server and database connection details, provide selections on what needs mirrored into Fabric, either all data or user selected eligible mirrored tables. And, just like that mirroring is ready to go. Mirroring SQL Server database creates an initial snapshot in Fabric OneLake after which data is kept in sync in near-real time with every transaction when a new table is created/dropped, or data gets updated.

Mirroring for SQL Server (2016-2022) in Microsoft Fabric

Mirroring for SQL Server to Fabric from these SQL Server versions relies on the Change Data Capture (CDC) technology available in SQL Server. CDC captures an initial snapshot of all the tables selected for mirroring and there after replicate the changes. Additionally, on-premises data gateway (OPDG) is required to be installed in your SQL Server environment. The mirroring services connects to OPDG to read the initial snapshot as well as the changes and pulls the data into OneLake and converts into an analytics-ready format in Fabric.

For detailed steps (including pre-requisites) to configure, and monitor mirroring from SQL Server to Fabric, refer to the Mirrored SQL Server documentation.

SQL Server 2022 mirroring setup and replication in action:

Mirroring for SQL Server 2025 in Fabric

While the main functionality and experience stays the same as above, mirroring from SQL Server 2025 uses change feed instead of Change Data Capture. This is the same technology used in mirroring for Azure SQL in Fabric. In this version, SQL Server keeps track and replicates the initial snapshot and changes to the landing zone in OneLake which is then converted to an analytics-ready format by the mirroring engine in Fabric. On-premises data gateway is primarily used as a control plane to connect and authenticate your on-premises environment to Fabric. Arc Agent is required for outbound authentication from SQL Server to Fabric.

SQL Server 2025 mirroring setup and replication in action:

For detailed steps (including pre-requisites) to configure, monitor and troubleshooting mirroring from SQL Server 2025 data to Fabric, refer to the Mirrored SQL Server documentation.

The table below summarizes the differences between various SQL sources when mirroring to Fabric.

From here on, the mirrored data in the delta format is ready for immediate consumption across all Fabric experiences and features like Power BI with new Direct Lake mode, Data Warehouse, Data Engineering, Lakehouse, KQL Database, Notebooks and copilots work instantly.

Resources:

What’s new with Mirroring at Microsoft Build 2025 – Mirroring in Fabric – What’s new

Try out Mirroring in Fabric, sign up for a free trial and get started.

Download the SQL Server 2025 preview.

The post Mirroring for SQL Server in Microsoft Fabric (Preview) appeared first on Microsoft SQL Server Blog.

Understanding Embeddings

Embeddings are numerical representations of data that capture the semantic meaning of the information. For example, in natural language processing, words or phrases are converted into vectors (embeddings) that reflect their meanings and relationships to other words. This allows for more efficient and meaningful data analysis, as similar concepts are represented by vectors that are close to each other in the vector space.

Understanding KNN and ANN

To appreciate the significance of DiskANN, it’s essential to understand the difference between K-Nearest Neighbors (KNN) and Approximate Nearest Neighbors (ANN).

K-Nearest Neighbors (KNN) is a traditional algorithm used to find the exact nearest neighbors of a query point in a dataset. While KNN is precise, it can be computationally expensive and slow, especially with large datasets.

Approximate Nearest Neighbors (ANN), on the other hand, aims to find neighbors that are close enough to the query point but not necessarily the exact nearest ones. ANN algorithms trade off a bit of accuracy for a significant gain in speed and efficiency, making them suitable for large-scale applications.

The Concept of Vector Index

In SQL Server 2025, we introduce the concept of a “vector index”. Unlike a traditional B-tree index, which is used for exact match queries, a vector index is designed to optimize the search for similar vectors. This index helps avoid querying vectors that are unlikely to be relevant to the given query, thereby improving search efficiency and performance.

Importance of Recall in Vector Index Performance

When evaluating the performance of a vector index, it’s crucial to consider not just the speed at which results are returned, but also the quality of those results. This quality is often measured by a metric called recall. Recall is defined as the proportion of relevant items that are successfully retrieved by the search algorithm. In other words, it measures how many of the expected relevant vectors are actually returned by the search.

For example, if we expect to retrieve 10 relevant vectors for a given query, and the search returns 9 of them, the recall is 0.9 or 90%. High recall is essential for ensuring that the search results are comprehensive and include all relevant items. This is particularly important in applications where missing relevant results could lead to significant issues or missed opportunities.

Introducing DiskANN

DiskANN is a suite of scalable, accurate and cost-effective approximate nearest neighbor search algorithms specifically designed for large-scale vector search and recommendation systems. The algorithm is detailed in the research project “DiskANN: Vector Search for Web Scale Search and Recommendation“. DiskANN leverages disk storage to efficiently find similar data points in large datasets, making it ideal for applications that require fast and scalable vector search capabilities.

Key Features of DiskANN in SQL Server 2025

• Integration: DiskANN is seamlessly integrated into SQL Server 2025, allowing users to leverage this powerful algorithm using familiar T-SQL syntax.
• High Recall: DiskANN achieves the best in class recall rates, ensuring that the majority of relevant vectors are retrieved during searches.
• Enterprise Security: Having DiskANN in SQL Server means you can use all the enterprise security features of SQL Server, from Row Level Security to Transparent Data Encryption, to safely store all your data, including vectors and embeddings. This integration reduces security risks, increases efficiency, and ensures compliance with industry standards.

Test drive DiskANN yourself

We invite you to explore the public preview of DiskANN in SQL Server 2025 and experience the enhanced capabilities it brings to your data search and recommendation systems. You can find full end-to-end samples here: https://github.com/Azure-Samples/azure-sql-db-vector-search. Make sure to check out the latest documentation for SQL Server 2025 here:  What’s new in SQL Server 2025 Preview

The post Announcing Public Preview of DiskANN in SQL Server 2025 appeared first on Microsoft SQL Server Blog.

The Microsoft Connector for Oracle enables data export from and import into Oracle databases within an SSIS package. This feature, available in Enterprise editions of SQL Server 2019 and 2022, will remain functional for the lifecycle of the SQL Server product. However, support for this feature will officially end on July 4, 2025. With the deprecation, future product releases will provide no further bug fixes. Additionally, it will not be supported from SQL Server 2025 and onwards.

Today, customers are leveraging the Microsoft Connector for Oracle in a variety of scenarios, including integrating Oracle data with other sources and supporting ETL (Extract, Transform, Load) processes to gain valuable insights. We recommend that customers use the SSIS ADO.NET Source and ADO.NET Destination components as the primary alternative solution to the Microsoft Connector for Oracle.

These SSIS ADO.NET components offer similar ETL capabilities for connecting Oracle databases with a .NET provider, specifically the OracleClient Data Provider, to connect, transfer, and transform your data efficiently. For further detailed instructions, please refer to the step-by-step guide.

If you need any assistance, please contact Microsoft Support.

Microsoft SQL Server

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Exploring best-in-class connectivity to Oracle with Microsoft Fabric 

The announcement of the deprecation of the SQL Server Integration Services (SSIS) Microsoft Connector for Oracle also presents an opportunity to explore new solutions for modern data integration with Oracle.

Microsoft Fabric is an end-to-end analytics and data platform designed for enterprises that require a unified solution. It encompasses data movement, processing, ingestion, transformation, real-time event routing, and report building. It offers a comprehensive suite of services including Data Engineering, Data Factory, Data Science, Real-Time Analytics, Data Warehouse, and Databases. 

Data Factory in Microsoft Fabric offers a modern data integration experience with Oracle databases, allowing reading from Oracle databases on-premises or behind a virtual network, and writing to any data destination.

Mirroring in Microsoft Fabric allows users to enjoy a highly integrated, end-to-end, and easy-to-use product that is designed to simplify your analytics needs. You can continuously replicate your existing data estate directly into Fabric’s OneLake, which can be used for all your analytical needs. This feature allows businesses to continuously integrate their existing data estate without complex ETL. 

Let’s explore the details of each of the approaches below. 

Oracle connectivity with Data Factory

Data Factory in Microsoft Fabric provides a modern data integration experience to ingest, prepare, and transform data from a rich set of data sources. It incorporates the simplicity of Power Query, and you can use more than 200 native connectors to connect to data sources on-premises and in the cloud.

One of the powerful features of Data Factory is its ability to configure and manage Oracle database connections in a copy activity. This functionality allows organizations to seamlessly integrate their Oracle databases into their data pipelines, ensuring efficient data movement and transformation. Configure Oracle database in a copy activity provides comprehensive instructions on how to perform this configuration. 

You can leverage the on-premises data gateway to securely connect to your on-premises Oracle database. This gateway acts as a bridge, enabling seamless data movement between on-premises data sources and cloud services. For detailed instructions, please refer to move data from Oracle to Fabric Lakehouse via pipeline and on-premises data gateway.

Replicating Oracle data into Fabric’s OneLake with Mirroring 

Mirroring in Microsoft Fabric offers a modern approach to seamlessly accessing and ingesting data from any database or data warehouse into OneLake in Microsoft Fabric. This feature allows businesses to continuously integrate their existing data estate without complex ETL processes. 

Open Mirroring in Fabric is extensible, customizable, and built on the open Delta Lake table format. It enables applications and data ISVs (Independent Software Vendors) to write change data directly into a mirrored database in Fabric using public APIs (Application Programming Interface). Once the data lands in OneLake, Open Mirroring handles complex data changes, ensuring all mirrored data remains continuously up-to-date and ready for analysis. 

We are thrilled to see Oracle Golden Gate streamline the delivery of mirroring solutions in Microsoft Fabric by integrating their data solution into Open Mirroring. As a key partner in our Open Mirroring ecosystem, Oracle Golden Gate offers a powerful and seamless approach to data replication, enabling continuous and efficient integration of data into Microsoft Fabric’s OneLake. This partnership highlights our commitment to providing modern, extensible solutions that simplify data integration and drive value for our customers. 

Simplifying Oracle to SQL Server Migration: Leveraging Microsoft SQL Server Migration Assistant (SSMA)

Additionally, if you are looking to migrate Oracle Database to SQL Server, Microsoft SQL Server Migration Assistant (SSMA) is a tool designed to automate database migration. SQL Server Migration Assistant (SSMA) for Oracle is a comprehensive environment that helps you quickly migrate Oracle databases to SQL Server, Azure SQL Database. The Oracle to SQL Server migration guide provides detailed instructions on how to migrate your Oracle database to SQL Server using SSMA for Oracle. This comprehensive guide ensures a smooth transition, minimizing disruptions and maximizing efficiency.

Looking forward

The deprecation of the SSIS Microsoft Connector for Oracle offers an opportunity to explore and implement more advanced and robust data integration solutions. By considering the ADO.NET components, Microsoft Fabric, or Microsoft SQL Server Migration Assistant for Oracle, organizations can ensure continued efficiency and reliability in their data integration processes. Each of these alternatives brings unique benefits, allowing businesses to choose the one that best aligns with their operational requirements and strategic goals. 

As the landscape of data integration evolves, staying informed about the latest tools and technologies will be crucial for maintaining a competitive edge and achieving seamless data connectivity. By proactively addressing the deprecation and selecting the appropriate alternative, organizations can continue to leverage their data assets effectively and drive business success. 

Resources 

Learn more about Data Factory in Microsoft Fabric and Oracle to SQL Server migration

• Load data from or into Oracle database—SQL Server Integration Services (SSIS) | Microsoft Learn 

• What is Microsoft Fabric—Microsoft Fabric | Microsoft Learn

• Data Factory in Microsoft Fabric documentation—Microsoft Fabric | Microsoft Learn 

• Configure Oracle database in a copy activity—Microsoft Fabric | Microsoft Learn 

• Move data from Oracle to Fabric Lakehouse via pipeline and on-premises data gateway—Microsoft Fabric | Microsoft Learn 

• Mirroring—Microsoft Fabric | Microsoft Learn

• Introducing Open Mirroring in Microsoft Fabric | Microsoft Fabric Blog | Microsoft Fabric 

• Open Mirroring (Preview) Partner Ecosystem—Microsoft Fabric | Microsoft Learn

• Oracle to SQL Server: Migration guide—SQL Server | Microsoft Learn

• Migrating Oracle Databases to SQL Server (OracleToSQL)—SQL Server | Microsoft Learn

The post SQL Server Integration Services (SSIS) Microsoft Connector for Oracle deprecation  appeared first on Microsoft SQL Server Blog.

Microsoft SQL Server 2025, now in preview, is an enterprise AI-ready database from ground to cloud that tackles these challenges by bringing AI to customers’ data. This release continues SQL Server’s three decades of innovation in performance and security, adding new AI capabilities. With Microsoft Fabric integration, customers can bring their data into the next generation of data analytics. The release supports hybrid environments across clouds, on-premises datacenters, and edge, leveraging Microsoft Azure innovation for customers’ databases.

Over the years, SQL Server has transcended well beyond a traditional relational database. With the latest release of SQL Server, we’re enabling customers to build AI applications deeply integrated with the SQL engine. SQL Server 2025 is transforming into a vector database in its own right, using the built-in filtering capabilities along with a vector search, with great performance and is easily consumable by developers using T-SQL.

AI built-in

This new version has AI built-in, simplifying AI application development and retrieval-augmented generation (RAG) patterns with secure, performant, and easy-to-use vector support, leveraging familiar T-SQL syntax. With this new capability, you can combine vectors with your SQL data for a hybrid AI vector search.

Build AI applications with your enterprise database

SQL Server 2025 is an enterprise-ready vector database with built-in security and compliance, bringing enterprise AI to your data. It features a native vector store and index powered by DiskANN, a vector search technology using disk storage to efficiently find similar data points in large datasets. These databases efficiently support chunking and enable accurate data retrieval through semantic searching. In this latest SQL Server version, flexible AI model management within the engine using Representational State Transfer (REST) interfaces allows you to use AI models from ground to cloud.

In addition, whether customers are working on data preprocessing, model training, or RAG patterns, extensible, low-code tools offer flexible model interfaces within the SQL engine, supported by T-SQL and external REST endpoints. These tools enhance developers’ ability to create various AI applications through seamless integration with popular AI frameworks like LangChain, Semantic Kernel, and Entity Framework Core.

Boost developer productivity

When building data-intensive applications such as AI applications, it’s critical to focus on extensibility, frameworks, and data enrichment to enhance developers’ productivity. We ensure SQL will provide a best-in-class experience for developers by incorporating features such as REST API support, GraphQL integration through Data API Builder, and Regular Expression enablement. Additionally, native JSON support enables developers to more effectively deal with frequently changing schema and hierarchical data, facilitating the creation of more dynamic applications. Overall, we’re enhancing SQL development to be more extensible, performant, and user-friendly. All functionalities are underpinned by the security provided by the SQL Server engine, making it a truly enterprise-ready platform for AI.

Best-in-class security and performance

SQL Server 2025 is an industry leader in database security and performance. Support for Microsoft Entra managed identities improves credential management, reduces potential vulnerabilities, and provides compliance and auditing capabilities. SQL Server 2025 introduces outbound authentication support for MSI (Managed Service Identity) for SQL Server enabled by Azure Arc.

We’re also introducing performance and availability enhancements, extensively battle-tested on Microsoft Azure SQL, to SQL Server. In the new version you can boost workload performance and reduce troubleshooting with enhanced query optimization and query performance execution. Optional Parameter Plan Optimization (OPPO) is designed to enable SQL Server to choose the optimal execution plan based on customer-provided runtime parameter values and to significantly reduce bad parameter sniffing problems that can exist in workloads. Persisted statistics on secondary replicas prevent the loss of statistics during a restart or failover, thereby avoiding potential performance degradation. Regarding query execution, the improvements in batch mode processing and columnstore indexing further establish SQL Server as a mission-critical database for analytical workloads.   

Optimized locking reduces lock memory consumption and minimizes blocking for concurrent transactions through Transaction ID (TID) Locking and Lock After Qualification (LAQ). This capability enables customers to increase uptime and enhance concurrency and scale for SQL Server applications. 

Change event streaming for SQL Server brings real-time application integration with event driven architectures, command query responsibility segregation, and real-time intelligence. This will add new database engine capabilities to capture and publish incremental changes to data and schema to a provided destination such as Azure Event Hubs and Kafka in near real-time.

Microsoft Fabric and Azure Arc connected

In traditional data warehouse and data lake scenarios, integrating all your data involves designing, monitoring, and managing complex ETL (Extract, Transform, Load) processes to transfer operational data from SQL Server. These traditional methods do not support real-time data transfer, resulting in latency that prevents the creation of real-time analytics. Microsoft Fabric offers comprehensive, integrated, and AI-enhanced data analytics services designed to meet modern requirements of analytical workloads. Mirrored SQL Server Database in Fabric is a fully managed, resilient process that simplifies SQL Server data replication to Microsoft OneLake in near real-time. Mirroring will enable customers to continuously replicate data from SQL Server databases running on Azure virtual machines or outside of Azure, serving online transaction processing (OLTP) or operational store workloads directly into OneLake in order to facilitate analytics and insights on the unified Fabric data platform.

Azure continues to be a critical component of SQL Server. With Azure Arc, SQL Server 2025 will continue to offer cloud capabilities to enable customers better manage, secure, and govern their SQL estate at scale across on-premises and cloud. Capabilities like automatic patching, automatic backups, monitoring, and Best Practices Assessment offer customers more ways to streamline routine tasks and further enhance their business continuity. In addition, Azure Arc simplifies SQL Server licensing by offering a pay-as-you-go option, bringing flexibility and licensing visibility to our customers.

Sign up for the preview today

We’re currently onboarding customers and partners to SQL Server 2025 preview, in advance of general availability in the coming year. 

Register today to apply for the SQL Server 2025 Community Technology Preview (CTP)¹ and stay informed about SQL Server 2025 updates.

Microsoft just announced the upcoming release of SQL Server Management Studio (SSMS) 21 Preview 1. This release integrates Microsoft Copilot capabilities into SSMS. The Copilot experience streamlines SQL development by offering real-time suggestions, code completions, and best practice recommendations. If you would like to take part and have an early hands-on experience with this new capability, please use this link to indicate your interest.

¹Some of the new capabilities covered in this blog may not be available in the first CTP version.

The post Announcing Microsoft SQL Server 2025: Enterprise AI-ready database from ground to cloud appeared first on Microsoft SQL Server Blog.

By migrating their databases to Azure, customers like Ernst and Young are modernizing their data estate and leveraging cutting-edge cloud innovations. However, the migration process can be complex, whether moving within the same database management system (homogeneous) or between different systems (heterogeneous). Microsoft offers a suite of tools for migration to simplify the migration process. To further enhance the user experience, we are streamlining the Azure database migration tools ecosystem. This involves retiring certain overlapping tools to simplify finding the right tool and provide unified migration experiences across all phases of migration. As part of this effort, effective 12/15/2024 we are replacing some tools with unified experiences that offer capabilities across various migration stages in the drive to modernize their data estate and take advantage of innovation in the cloud.

Azure Database Migration Guides

Step-by-step guidance for modernizing your data assets

Learn more

With a refined set of tools, you can confidently plan, assess, and execute your database migration with minimal downtime, ensuring a smooth transition to Azure SQL. Post the 12/15/24, retirement date, Microsoft will stop supporting these tools for any issues that arise and will not issue any bug fixes or further updates. Here is the list of tools that are planned for retirement and Microsoft recommended replacement tools.

Microsoft recommended tools for migration to Azure SQL

With the retirement of Database Migration Assistant for Oracle (DMAO), Database Schema Conversion Toolkit (DSCT), Data Access Migration Toolkit (DAMT), Database Experimentation Assistant (DEA), the Azure database migration tooling ecosystem is greatly simplified. Here is Microsoft’s recommendation for database migration tools for customers moving to Azure SQL. 

Homogenous migrations (SQL Server to Azure SQL) 

If the SQL Server that will be migrated is already enabled by Azure Arc, you can use Arc capabilities to perform a migration assessment and get optimal Azure SQL Target recommendations. Additionally, SQL Server enabled by Azure Arc provides multiple Azure benefits to SQL Servers outside Azure like automated backups and patching, Microsoft Defender for SQL, inventory of instances and databases, and Entra ID support. By enabling these Arc features, you can leverage cloud automation and security for Azure SQL Server even before you migrate. 

If the SQL Server outside Azure is not inventoried yet, you can use Azure Migrate for discovery, assessment and business case to know the right Azure SQL targets for your on-premises SQL Workloads and to get the projected cost savings of migrating to Azure SQL.

To migrate SQL Server into an Azure Virtual Machine with the same configuration as the source, users can use Azure Migrate to perform lift and shift migrations. SQL Server on Azure Virtual Machines allows you to easily migrate your SQL Server workloads to the cloud, offering SQL Server’s performance and security along with Azure’s flexibility and hybrid connectivity to address urgent business needs. Later you can evaluate one of the Azure SQL PaaS targets (Azure SQL Managed Instance, Azure SQL Database) and modernize to a PaaS service for better cost and workload performance optimizations. 

If you have completed an assessment and are ready to move to Azure SQL Managed Instance or Azure SQL Database, you can start your migration journey with Azure Migrate, you can use Azure Database Migration service or Azure SQL Migration extension for Azure Data Studio can be used. 

If the SQL Server estate is already inventoried, users can use Azure SQL Migration extension for Azure Data Studio to complete the entire migration journey i.e., perform assessment, get Azure SQL Target recommendations and perform migrations.

Heterogenous migrations (non-SQL Server databases to Azure SQL) 

With the availability of Target Assessment and SKU recommendation capabilities in SQL Server Migration Assistant (SSMA) along with existing code conversion and migration capabilities, SSMA becomes a single tool that you need to use to migrate from other source database platforms like Oracle, DB2, SAP ASE, MySQL, Access to Azure SQL or SQL Server. 

Learn more about modernizing your databases with Azure

• Get step-by-step guidance for modernizing your Oracle and SQL Server databases to Azure in the Azure Database Migration Guides.
• Read about the Azure Migrate Assessment for Azure SQL to get an overview of SQL Server assessment process using Azure Migrate.
• Know how to complete end to end SQL Server to Azure SQL migration journey with Azure SQL Migration extension for Azure Data Studio. 
• Find documentation for SQL Server Migration Assistant (SSMA), a tool for assessing and automating migration from Microsoft Access, DB2, MySQL, Oracle, and SAP ASE.

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