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?

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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.

During recent years, Azure has undergone significant evolution, marked by groundbreaking innovations like Microsoft Fabric and Azure Data Lake Storage. As we continue this journey, it remains imperative to keep evolving our approach on hybrid data storage, ensuring optimal empowerment for our SQL Server customers in leveraging the best from Azure.

Retirement of SQL Server Stretch Database 

On November 16, 2022, the SQL Server Stretch Database feature was deprecated from SQL Server 2022. For in-market versions of SQL Server 2019 and 2017, we had added an improvement that allowed the Stretch Database feature to stretch a table to an Azure SQL Database. Effective July 9, 2024, the supporting Azure service, known as SQL Server Stretch Database edition, is retired. Impacted versions of SQL Server include SQL Server 2022, 2019, 2017, and 2016.  

In July 2024, SQL Server Stretch Database will be discontinued for SQL Server 2022, 2019, 2017, and 2016. We understand that retiring an Azure service may impact your current workload and use of Stretch Database. Therefore, we kindly request that you either migrate to Azure or bring their data back from Azure to your on-premises version of SQL Server. Additionally, if you’re exploring alternatives for archiving data to cold and warm storage in the cloud, we’ve introduced significant new capabilities in SQL Server 2022, leveraging its data virtualization suite. 

The path forward 

SQL Server 2022 supports a concept named CREATE EXTERNAL TABLE AS SELECT (CETaS). It can help customers archive and store cold data to Azure Storage. The data will be stored in an open source file format named Parquet. It operates well with complex data in large volumes. With its performant data compression, it turns out to be one of the most cost-effective data storage solutions. Using OneLake shortcuts, customers then can leverage Microsoft Fabric to realize cloud-scale analytics on archived data.  

Our priority is to empower our SQL Server customers with the tools and services that leverage the latest and greatest from Azure. If you need assistance in exploring how Microsoft can best empower your hybrid data archiving needs, please contact us.

New solution FAQs

What’s CETaS? 

Creates an external table and then exports, in parallel, the results of a Transact-SQL SELECT statement. 

• Azure Synapse Analytics and Analytics Platform System support Hadoop or Azure Blob Storage.
• SQL Server 2022 (16.x) and later versions support CETaS to create an external table and then export, in parallel, the result of a Transact-SQL SELECT statement to Azure Data Lake Storage Gen2, Azure Storage Account v2, and S3-compatible object storage. 

What is Fabric? 

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. Fabric offers a comprehensive suite of services including Data engineering, Data Factory, Data Science, Real-Time Analytics, Data Warehouse, and Databases. 

With Fabric, you don’t need to assemble different services from multiple vendors. Instead, it offers a seamlessly integrated, user-friendly platform that simplifies your analytics requirements. Operating on a software as a service (SaaS) model, Fabric brings simplicity and integration to your solutions. 

Fabric integrates separate components into a cohesive stack. Instead of relying on different databases or data warehouses, you can centralize data storage with Microsoft OneLake. AI capabilities are seamlessly embedded within Fabric, eliminating the need for manual integration. With Fabric, you can easily transition your raw data into actionable insights for business users. 

What is OneLake shortcuts?  

Shortcuts in OneLake allow you to unify your data across domains, clouds, and accounts by creating a single virtual data lake for your entire enterprise. All Fabric experiences and analytical engines can directly connect to your existing data sources such as Azure, Amazon Web Services (AWS), and OneLake through a unified namespace. OneLake manages all permissions and credentials, so you don’t need to separately configure each Fabric workload to connect to each data source. Additionally, you can use shortcuts to eliminate edge copies of data and reduce process latency associated with data copies and staging. 

Shortcuts are objects in OneLake that point to other storage locations. The location can be internal or external to OneLake. The location that a shortcut points to is known as the target path of the shortcut. The location where the shortcut appears is known as the shortcut path. Shortcuts appear as folders in OneLake and any workload or service that has access to OneLake can use them. Shortcuts behave like symbolic links. They’re an independent object from the target. If you delete a shortcut, the target remains unaffected. If you move, rename, or delete a target path, the shortcut can break. 

Learn more 

• Stretch Database
• Deprecated database engine features in SQL Server 2022
• Install an on-premises data gateway
• SQL Server in Microsoft Fabric? Use CETaS to move data!
• OneLake shortcuts
• CREATE EXTERNAL TABLE AS SELECT (CETaS)

Microsoft Fabric

Bring your data into the era of AI

Explore solutions

The post Announcing the retirement of SQL Server Stretch Database appeared first on Microsoft SQL Server Blog.

Azure Data Studio

A modern open-source, cross-platform hybrid data analytics tool designed to simplify the data landscape.

Learn more

Connectivity

The migration from the Active Directory Authentication Library (ADAL) to Microsoft Authentication Library (MSAL) was a significant undertaking by the team. This was necessary as ADAL support ends in June of this year, and it provides multiple benefits for those environments using Azure Activity Directory (AAD). AAD users should notice an improved and more reliable experience, particularly around token refresh and connection stability. This also helped us fix an issue in the MySQL extension for AAD. 

Additional changes include improved loading of Azure resources and new Dedicated SQL Pools and Azure Synapse Analytics nodes in the Azure tree. Azure Data Studio 1.41 also provides the ability to customize the name of firewall rules for Azure SQL and adds support for connecting to a server alias (versus a server name).

If you have applications that use ADAL, please see the Migrate applications to the Microsoft Authentication Library (MSAL) page for more information.

Object explorer

A new area of focus in this release is Object Explorer (OE), and this will continue to be an area we improve upon in the next few releases. Those with serverless Azure SQL previously reported issues with folders not expanding correctly, and with databases being brought online (thus incurring costs) when it was not expected. Other users noted that expanding OE timed out after 45 seconds. We have addressed all these issues in this release, in addition to adding support for Ledger Views.

Query results

The query results window got a fair bit of attention this release as we work through the backlog of open issues. First, we introduced a new configuration option to show or hide the action bar in the query results view. The Query Editor > Results: Show Action Bar option can be found in the command palette (CTRL + , ) if you type Show Action Bar. By default, the action bar is shown in the query results pane, as seen in the screenshot below:

There are also improvements around opening JSON files and the visibility of the horizontal scroll bar in the query results pane. Azure Data Studio 1.41 now correctly handles line breaks in cells when copying from the results grid and pasting to an editor, and the auto-resizing of columns in the output pane has been updated to better display column contents. Finally, cell selection and navigation in the results grid have been enhanced, and we introduced additional summary details when selecting multiple cells in the results window:

Extensions

Multiple teams have been working on updates to various extensions available from Azure Data Studio.  For SQL Projects, we have improved the experience of finding projects by providing a dropdown that lists saved projects, rather than requiring users to browse to their location. We had reports that differences in schema compare were not highlighted correctly, and that problem has been fixed.

Users of the SQL Migration extension will see an improvement in the migration process as we better support migrations to specific subscriptions (such as government), and the extension now includes the Premium Series Memory Optimized SQL MI SKU as a recommendation where appropriate.

MongoDB and Microsoft Azure continue to build on their partnership by introducing an extension for MongoDB Atlas and Azure Data Studio on the Azure Marketplace. This Extension is available in Public Preview as of today, Wednesday, January 25, 2023.  You already know that Azure Data Studio is a modern open-source, cross-platform hybrid data analytics tool designed to simplify your data landscape, and customers can use Azure Data Studio to work with their data sitting in one or more Azure data services. MongoDB Atlas on Azure provides a fully managed solution for MongoDB in the cloud, and you can now seamlessly connect to and query data on MongoDB Atlas right from Azure Data Studio. This allows you to interact with data on MongoDB Atlas alongside other data services and provides a unified view of your data estate.  If you are an Azure customer that is curious about building applications with MongoDB Atlas and want to amplify your integrated experience inside Azure Data Studio, try Pay-As-You-Go Atlas on the Azure Marketplace today!

With this 1.41 release, the Polyglot Notebooks extension will be removed from the Azure Data Studio Extension Marketplace. For a polyglot notebooks experience, we recommend folks use the Polyglot Notebooks in Visual Studio Code.

Odds and ends

Continuing on our path of adding support for arm64, we now include support for arm64 on Windows.  Whether you run iOS or Windows, Azure Data Studio 1.41 now provides the capability to leverage arm64, resulting in improved performance.

We are pleased to see users embracing Table Designer and Query Plan Viewer, two features that became generally available (GA) in the November release. In 1.41 we fixed an issue related to opening Table Designer for Ledger tables, and one related to creating a table when another table with the same name already exists.

There were also two requests specific to Query Plan Viewer that got attention in this release. When saving query plan files from Azure Data Studio, we now incrementally append a number to the end of the file for unique naming, and we’ve altered the default folder location when saving plans for a more consistent experience.

Lastly, we had previously announced that we were removing Big Data Cluster functionality from Azure Data Studio. This removal has been delayed until a later release.

Looking forward

We are already at work on the next release of Azure Data Studio and are making plans for what we want to accomplish in 2023. You can expect that we will continue to review backlog issues and address them as they relate to an existing area of focus. We have more changes coming related to the connection dialog and object explorer, and you will also see improvements in user management. Finally, if you see a comment on an issue you opened–whether recent or ages ago–please feel free to respond and provide more information if you are able. 

The post Azure Data Studio 1.41 release appeared first on Microsoft SQL Server Blog.

Today, we announced the general availability of SQL Server 2022, the most Azure-enabled release of SQL Server yet, with continued innovation across performance, security, and availability¹. This marks the latest milestone in the more than 30-year history of SQL Server.

SQL Server 2022 is a core element of the Microsoft Intelligent Data Platform. The platform seamlessly integrates operational databases, analytics, and data governance. This enables customers to adapt in real-time, add layers of intelligence to their applications, unlock fast and predictive insights, and govern their data—wherever it resides.

SQL Server 2022’s connections to Azure², including Azure Synapse Link and Microsoft Purview make it easier for customers to drive deeper insights, predictions, and governance from their data at scale. Azure integration also includes managed disaster recovery (DR) to Azure SQL Managed Instance, along with near real-time analytics, allowing database administrators to manage their data estates with greater flexibility and minimal impact to the end user³.

Performance and scalability are automatically enhanced via built-in query intelligence. Security innovation, building on SQL Server’s track record as being the least vulnerable database over the last 10 years, continues with Ledger for SQL Server, which uses blockchain to create a tamper-proof track record of time of all changes to the database.

Watch how one of our customers, Mediterranean Shipping Company, is already taking advantage of the new capabilities in SQL Server 2022.

Azure-enabled features

Link feature for Azure SQL Managed Instance: To ensure uptime, SQL Server 2022 is fully integrated with the new link feature in Azure SQL Managed Instance. With this new capability, you benefit from a PaaS environment applied to disaster recovery—allowing you to spend less time on setup and management even when compared to an IaaS environment. This works by using a built-in Distributed Availability Group (DAG) to replicate data to a previously deployed Azure SQL Managed Instance as a DR replica site. The instance is ready and waiting for whenever you need it—no lengthy configuration or maintenance required. You can also use this link feature in read scale-out scenarios to offload heavy requests that might otherwise affect database performance. We are working on building out more capabilities to support online disaster recovery.

Azure Synapse Link for SQL: Previously, moving data from on-premises databases, like SQL Server, to Synapse required you to use extract, transform, and load (ETL). Configuring and running an ETL pipeline is time-consuming, and insights often lag behind what is happening at any moment. Azure Synapse Link for SQL Server 2022 provides automatic change feeds to capture the changes within SQL Server and feed them into Azure Synapse Analytics. Synapse Link provides near real-time analysis and hybrid transactional and analytical processing with minimal impact on operational systems. Once the data comes to Synapse, you can combine it with many different data sources, regardless of their size, scale, or format, and run powerful analytics over all of it using your choice of Azure Machine learning, Spark, or Power BI. Because the automated change feeds only push what is new or different, data transfer occurs much faster and allows for near real-time insights, all with minimal impact on the performance of the source database in SQL Server 2022.

“Synapse Link for SQL Server 2022 helps us to seamlessly replicate operational data in near real-time to be able to have more powerful analytics.”—Javier Villegas, IT Director for DBA and BI Service, Mediterranean Shipping Company.

Microsoft Purview integration: Microsoft Purview is a unified data governance and management service. We are excited to highlight that SQL Server is also integrated with Microsoft Purview for greater data discovery, allowing you to break down data silos. Through this integration you will be able to:

• Automatically scan your on-premises SQL Server for free to capture metadata.
• Classify your data using built-in and custom classifiers and Microsoft Information Protection sensitivity labels.
• Set up and control specific access rights to SQL Server.

Additional Azure-connected features: SQL Server 2022 has a number of additional Azure-enabled features. A simple connection to the Azure Arc agent, part of the default setup process for SQL Server 2022, enables additional capabilities, including:

• Single view of all SQL Servers deployed on-premises, in Azure and other clouds.
• Fully automated technical assessment for SQL Server at no additional cost, to help you optimize your database’s performance, scalability, security, business continuity, and more.
• Protect your on-premises data using Microsoft Defender for Cloud.
• Secure identities with Single Sign-On and Azure Active Directory.
• Pay-as-you-go billing.

Continued innovation to the core SQL Server engine

Performance: Performance is critical. On the SQL Server Engineering team, our core engine feature principles are: do no harm, no app changes required. With SQL Server 2022, performance enhancements come without requiring code changes by the end user.

SQL Server continues to offer differentiated performance, with #1 OLTP performance, #1 Non-Clustered DW performance on 1TB, 3TB, 10TB, and 30TB according to the independent Transaction Processing Performance Council. In SQL Server 2022:

• With Query Store, we are adding support for read replicas and enabling query hints to improve performance and quickly mitigate issues without having to change the source T-SQL.
• With Intelligent Query Processing, we’re expanding more scenarios based on common customer problems. For example, the “parameter sensitive plan” problem refers to a scenario where a single cached plan for a parameterized query is not optimal for all possible incoming parameter values. With SQL Server 2022’s Parameter Sensitive Plan optimization feature, we automatically enable the generation of multiple active cached plans for a single parameterized statement. These cached execution plans will accommodate different data sizes based on the provided runtime parameter values.

“As a company with 24/7 availability requirements, we are looking forward to embracing all SQL Server 2022 features that can make database failover faster, such as Buffer Pool Parallel Scan, ParallelRedo and Accelerated Database Recovery (ADR) enhancements. On the development side, we expect to further utilize continuous improvements in the Intelligent Query Processing package. In an environment with a lot of servers and huge databases, even when you have people and resources to deal with performance issues, each feature that can improve performance or fix performance issues automatically or without touching the code is very valuable.” —Milos Radivojevic, Head of MSSQL Database Engineering at Entain.

Security: Over the past ten years, SQL Server has had few vulnerabilities. Building on this, the new Ledger for SQL Server feature creates a tamper-evidence track record of data modifications over time. This detects tampering by malicious actors and is beneficial for scenarios such as internal and external audits.

Availability: With Contained Availability Groups you can create an Always On availability group that manages its own metadata objects (users, logins, permissions) at the availability group level in addition to the instance level with contained availability groups. Additionally, it keeps multi-write environments running smoothly when you have users across multiple locations. With SQL Server 2022, we are automating the last-writer wins rule to ensure that when a conflict is detected, the most recent modification time will be chosen to be persisted on all replicas.

New pay-as-you-go SQL Server billing model, enabled by Azure Arc

Today, we are also excited to announce a new billing model that provides flexibility to innovate quickly and move as fast as you do.

Via a simple connection to Azure Arc, a default part of the SQL Server 2022 setup process, you now have access to a new cloud-enabled billing model for SQL Server, providing you with cost efficiency to pay only for what you use. Pay by the hour for consumption spikes and ad hoc usage without the need for upfront investment. Learn more in the announcement blog post.

Azure SQL migration offer

If you’re ready to start your journey to the cloud, Microsoft can help. Today we are announcing a new offer, the SQL + Apps Migration Factory. This program can assess and migrate qualifying low complexity SQL Server applications and databases to Azure SQL at no cost to you.⁴ Talk to your Microsoft account team or apply now at aka.ms/SQLAppsMigrationFactory to get started. 

SQL Server IoT 2022 

We are also announcing SQL Server IoT 2022, which is designed for fixed function use cases and licensed through the OEM channel under special dedicated use rights. You can read more about SQL Server IoT 2022.  

Learn more and get started with SQL Server 2022 today

• Learn more about SQL Server 2022 at the PASS Data Community Summit, including Microsoft and community-delivered keynote and general sessions.
• Visit the SQL Server 2022 website.
• Get ready for SQL Server 2022 by reading the documentation and watching SQL Server 2022 Data Exposed video series.
• Try out the Microsoft Learn SQL Server 2022 module and the SQL Server 2022 workshop.
• Get started today by deploying in Azure.
• Let us know if you have any thoughts or feedback through our SQL Server feedback portal.

Learn more about Azure SQL Managed Instance

• Learn about the November 2022 feature and other announcements at the PASS Data Community Summit.  
• Visit the Azure SQL Managed Instance website. 

^[1] SQL Server 2022 free editions (Developer edition, Express edition) are available to download starting today. SQL Server 2022 paid editions (Enterprise edition, Standard edition) will be available in Volume Licensing (Enterprise Agreement, Enterprise Agreement Subscriptions) and MPSA starting today, which represents the majority of SQL Server customers. Customers purchasing via CSP, OEM, and SPLA can begin purchasing SQL Server 2022 in January 2023.

^[2] For all Azure-connected features of SQL Server 2022, customers can optionally enable these capabilities based on business requirements.

^[3] The bidirectional disaster recovery capability of the Link feature for Azure SQL Managed Instance is available in limited public preview. Sign up for early access. General availability will occur at a future date.

^[4] Subject to the limitations described in the full SQL + Apps Migration Factory program specifications here, and provided that the SQL Server workloads are low complexity with no code changes, Microsoft agrees to assess and migrate SQL Server databases and SQL Server-associated applications from your datacenter or AWS EC2 to Azure at no cost to customer. Migrations must be completed by June 30, 2023. 

The post SQL Server 2022 is now generally available appeared first on Microsoft SQL Server Blog.

Part of the SQL Server 2022 blog series.

Traditionally, data to serve analytical systems have been extracted from operational data stores using custom-built extract, transform, and load (ETL) processes. These processes are often long-running, exert pressure on the source systems, and only run periodically in batch mode. While this kind of latency and overhead may be acceptable for some workloads, more and more companies are finding themselves in a place where they need to do analytics over operational data closer to real-time—something that traditional ETL systems cannot support.

Enter Azure Synapse Link for SQL.

Azure Synapse Link for SQL provides an automated way to extract data from source operational systems without having to build custom ETL processes. Some of the benefits of Azure Synapse Link for SQL are:

• Low code/no code solution: With Azure Synapse Link for SQL, you don’t need to build custom processes to extract the data and load it into an analytical system. You choose the tables that you want to replicate, specify how you want them stored in the target Azure Synapse Analytics dedicated SQL pool, and Azure Synapse Link for SQL takes care of the rest.
• Minimal impact on the source systems: We have strived to minimize the impact of data extraction from the source system. Where a traditional ETL process will run queries against the source tables, which can get expensive, Azure Synapse Link for SQL uses the new change feed functionality built into SQL Server 2022 and Azure SQL Database to get the data without having to run custom queries.
• Near-real-time data movement: Data is continually moved from the source systems into the Azure Synapse Analytics environment. Optionally, you can switch to “scheduled mode” if you don’t need near-real-time data movement.

How does it work?

Azure Synapse Link for SQL is powered by the new change feed functionality that has been added to SQL Server 2022 and Azure SQL Database. This functionality allows us to monitor tables for changes as they happen without the additional overhead that is brought along by a change data capture (CDC)–based data movement solution.

When a transaction is committed on a table that is being replicated by Azure Synapse Link for SQL, that transaction is written into a “landing zone,” which is a Gen2 Azure Data Lake storage (ADLS) account. From there, an ingestion service picks up the data and loads it into an Azure Synapse Analytics dedicated SQL pool. Once the data lands there, you can query the data like any other dedicated SQL pool.

Who will benefit?

Here are some examples of scenarios that would benefit from Azure Synapse Link for SQL:

• Database consolidation: Azure Synapse Link for SQL allows you to bring data from multiple source databases together into a single dedicated SQL pool for analytics. Whether you have multiple tenant databases that you want to use for market-based analytics, or you have grown by acquisition and have multiple source systems to bring together for analytics, Azure Synapse Link for SQL can bring all of that data together into a unified analytical platform.
• Hybrid on-premises/cloud: Since Azure Synapse Link for SQL supports both Azure SQL Database and SQL Server 2022, you can bring data into a common analytical system from wherever it lives.
• Near-real-time extension: If you have an ETL system that meets most of your needs but have a few tables where you want data to arrive closer to real-time, you could use Azure Synapse Link for SQL to transfer those tables from the source systems into the Azure Synapse Analytics dedicated SQL pool alongside the data that is processed in your nightly ETL system, and perform reporting an analytics tasks over all of the data.

How to learn more

• Read our technical blog post from the public preview launch.
• Check out our “getting started” documentation.
• Dig in with our How-To guides:
  • SQL Server 2022
  • Azure SQL Database

The post Azure Synapse Link for SQL appeared first on Microsoft SQL Server Blog.

This year, DPS 2020 features five parallel tracks focusing on Azure Data:

• Advanced Analytics
• Artificial Intelligence
• Azure Data Administration
• Azure Data Development
• Power BI

The virtual platform offers live Q and A, a networking lounge, a community zone, and technical round tables. Additionally, attendees will receive 12 month on-demand access to session recordings.

DPS 2020 offers an incredible opportunity to learn directly from our engineering teams, who will share the latest advances and insights on the Azure Data platform.

• Rohan Kumar will deliver the keynote. Rohan will highlight the latest innovations across the Microsoft Azure Data platform and share customer case studies. The keynote will also feature demos from multiple Microsoft engineers, including Anitha Adusumilli, Anna Hoffman, Buck Woody, Travis Wright, and Vasiya Krishnan.
• Microsoft Azure Data engineering teams will deliver over 35 sessions at DPS 2020. Hear the latest from the people who develop the tools you use every day, and engage in live discussions.
• Visit the virtual expo hall where you can connect with our team across SQL Server, Azure SQL, Azure Synapse Analytics, Power BI, and more.

Register now for a week of training at Data Platform Virtual Summit and receive twelve months of on-demand access to the DPS 2020 sessions.

The post Microsoft Azure at Data Platform Virtual Summit 2020 appeared first on Microsoft SQL Server Blog.

Today we are announcing the general availability of the highest requested feature for SQL Analytics in Azure Synapse, SQL Server Data Tools (SSDT) database projects. This release includes support for SQL Server Data Tools with Visual Studio 2019 along with native platform integration with Azure DevOps providing built-in continuous integration and deployment (CI/CD) capabilities for enterprise level deployments. This announcement also comes with support for the Schema Compare extension in Azure Data Studio for SQL Analytics.  You can now expect a frictionless development and deployment experience on any platform for your analytics solution.

Since announcing preview support for SQL Server Data Tools (SSDT), customers have been able to use popular SQL Server Data Tools features such as Schema Compare, build, and publish for local development of their data warehouse. Although this has helped customers accelerate project development, an automated build, test, and deployment infrastructure is still critical for continuous integration and deployment (CI/CD) scenarios. Without the native integration with Azure DevOps, customers were still forced to manually write PowerShell and TSQL scripts integrated with Azure DevOps for an automated release process.

With SQL Server Data Tools generally available and native Azure DevOps support, you can now set up stable release pipelines without any custom code, and changes to your data warehouse model can be safely and automatically promoted across development, testing, and production environments. Preview customers such as T-Mobile will now be able to accelerate their feature development with Azure Synapse.

“In our current environment, we would have needed hundreds of custom scripts to validate and promote changes across our test and production environments. We’re excited to now simply use SSDT, MSBuild, and the Publish task in Azure DevOps to deploy and release features to production on a consistent and faster cadence.” – Anthony Sabol, Director, Reporting & Analytics at T-Mobile.

Integrate with Microsoft Azure Repos for continuous integration 

Data engineers and developers can easily integrate their SQL Server Data Tools database projects with Microsoft Azure Repos. 

Configure continuous deployment using Microsoft Azure Pipelines 

Changes committed to source control in Azure Repos can automatically be pre-validated using MSBuild and promoted to target environments using Microsoft Azure Pipelines and the built-in SQL Analytics deployment task extension.  

Cross platform support for Schema Compare with Azure Data Studio 

Azure Data Studio is a cross-platform database tool that now allows you to compare the schema between two data warehouse definitions.  

Next steps

• Install Visual Studio 2019 for SQL Analytics to get started
• Set up source control integration with SQL Analytics by using Azure Repos
• Integrate a simple Azure Pipeline for continuous integration and deployment for SQL analytics capabilities within Azure Synapse
• Learn more about Azure Data Studio SQL Compare
• For feature requests and providing us feedback, please vote on our UserVoice

The post New in Azure Synapse Analytics: CICD for SQL Analytics using SQL Server Data Tools appeared first on Microsoft SQL Server Blog.

1. It’s consistent

Microsoft is a truly consistent hybrid platform, with the same code base across on-premises, Azure, and Azure Stack. With Azure Stack, you can extend Azure services and capabilities to on-premises environments without any code changes. Interoperability between SQL Server, SQL Server in an Azure Virtual Machine, and Azure SQL Database ensures business continuity and you can easily set up disaster recovery through Always On availability groups.

Download the Azure Stack datasheet

Set up disaster recovery for SQL Server

2. It’s frictionless

The task of migrating your databases to the cloud can be daunting. Microsoft can help you manage the migration seamlessly with several tools and services that simplify the process with minimal downtime. SQL Database Managed Instance provides easy re-hosting with no code changes, enabling a way to migrate huge databases into Azure without changing any code and staying compliant with your applications, without sacrificing performance.

Get started with SQL Database Managed Instance

Learn more about migrating a SQL Server database to SQL in Azure Virtual Machines

3. It’s cost-effective

SQL Server and Azure SQL Database are two of the most cost-effective hybrid data platforms with flexible pricing tiers. Leverage your on-premises licenses and migrate your Windows Server and SQL Server workloads to Azure and save with the Azure Hybrid Benefit (AHB). You can choose from different purchasing options and service tiers to fit your performance and cost needs.

Calculate your savings here with the Total Cost of Ownership (TCO) calculator

Allscripts, a leading healthcare software manufacturer, started using Microsoft Azure. In just three weeks, the company lifted and shifted dozens of acquired applications running on 1,000 virtual machines to Azure – migrating their on-premises applications to the cloud by taking advantage of Azure SQL Database Managed Instance.

“Using Azure has dramatically accelerated both our acquisition time and our new product development time. We’ve been able to shut down older, inefficient datacenters and focus more resources on developing great software. This is one factor that moves us ahead in a very competitive market.” – Peter Tomlinson, Director of IS, Technology Operations, Allscripts

Learn more about Allscripts’ hybrid data story

Try SQL Server on Azure Virtual Machine or SQL Database Managed Instance today, and manage your data seamlessly across on-premises and cloud.

The post Three reasons to choose Microsoft for your hybrid data platform appeared first on Microsoft SQL Server Blog.

Customers will get significantly improved query performance and enhanced security features with this release. APS AU7 builds on appliance update 6 (APS 2016) release as a foundation. Upgrading to APS appliance update 6 is a prerequisite to upgrade to appliance update 7.

Faster performance

APS AU7 now provides the ability to automatically create statistics and update of existing outdated statistics for improved query optimization. APS AU7 also adds support for setting multiple variables from a single select statement reducing the number of redundant round trips to the server and improving overall query and ETL performance time. Other T-SQL features include HASH and ORDER GROUP query hints to provide more control over improving query execution plans.

Better security

APS AU7 also includes latest firmware and drivers along with the hardware and software patch to address the Spectre/Meltdown vulnerability from our hardware partners.

Management enhancements

Customers already on APS2016 will experience an enhanced upgrade process to APS AU7 allowing a shorter maintenance window with the ability to uninstall and rollback to a previous version.
AU7 also introduces a section called Feature Switch in configuration manager giving customers the ability to customize the behavior of new features.

Flexibility of choice with Microsoft’s data warehouse portfolio

The latest update is an addition to already existing data warehouse portfolio from Microsoft, covering a range of technology and deployment options that help customers get to insights faster. Customers exploring data warehouse products can also consider SQL Server with Fast Track for Data Warehouse or Azure SQL Data Warehouse, a cloud-based fully managed service.

Next Steps

For more details about these features, please visit our online documentation.

The post Microsoft releases the latest update of Analytics Platform System appeared first on Microsoft SQL Server Blog.

mssql-cli is a new and interactive command line query tool for SQL Server. This open source tool works cross-platform and is part of the dbcli community.

mssql-cli auto-completion in action

In this release (v0.13.0), highlights include:

• Apt-get and Linux packaging support
• GDPR Compliance
• New demo video

Apt-get and Linux packaging support

One of the key issues Linux users run into when setting up mssql-cli for the first time is not having the right version of Python or having to install Python for the first time. We want to make the first experience with mssql-cli painless, thus we added apt-get support in order to package Python with your installation to help improve the acquisition experience.

For full instructions to acquire mssql-cli for each Linux distribution, please check out the Linux installation guide.

Note: For those who already installed mssql-cli via pip install, please run

sudo pip uninstall mssql-cli

Then, follow the installation instructions.

GDPR compliance

As many of us are familiar with, GDPR is approaching and we made some updates. In the past, file history stored entire T-SQL queries. However, if the query contained any secrets or passwords, it wasn’t smart enough to scrub those out. This is no longer the case, and now file history has been updated to no longer store secrets or passwords.

In addition, we have added 24-hour rotation of UserID when we collect telemetry.

New Channel9 video

One of our engineers, Abhi Abhishek, presented a demo of mssql-cli for Channel9, the Microsoft Developer studio. If you are new to mssql-cli, please check out this video and please share with those you feel would benefit from using this tool.

Contact us

We are open to any questions, feedback, or any feature suggestions for future releases, which can be submitted on our GitHub Issues. You can also Tweet at us @sqldatatools.

The post A new update for mssql-cli, an interactive CLI, is now available appeared first on Microsoft SQL Server Blog.