FabCon and SQLCon 2026: Unifying databases and Cloth on a single information platform

We’re deliver attendees collectively to share actual experiences and remedy challenges side-by-side. Solely collectively can we transfer into significant outcomes.

Welcome to the third annual FabCon and our first ever SQLCon right here in Atlanta, Georgia. With almost 300 workshops and periods, this joint occasion will spotlight how they’re bringing the facility of Microsoft SQL and Microsoft Cloth collectively to create a single, unified platform. However FabCon 2026 and SQLCon 2026 are about greater than product innovation. It’s about offering area for our 8,000 attendees to return collectively and share actual experiences, study from one another, and remedy challenges side-by-side. Solely collectively can we transfer past the hype and into significant outcomes.

The thrill surrounding this occasion displays the identical momentum we’re seeing throughout our information portfolio. Simply two and a half years after Microsoft Cloth reached common availability, it’s already serving greater than 31,000 prospects and stays the fastest-growing information platform in Microsoft’s historical past. Fortune 500 firms like The Coca-Cola Firm are already utilizing Cloth at scale throughout their organizations.

Microsoft Cloth helps us evolve our information basis right into a extra unified, AI-ready platform. Mixed with Energy BI and capabilities like Cloth IQ, it permits the enterprise to show information into intelligence and act on it quicker.

Shekhar Gowda, Vice President of International Advertising and marketing Applied sciences at The Coca-Cola Firm

Our databases are accelerating simply as shortly, with SQL Server 2025 rising greater than twice as quick because the earlier model.

At this time, we’re thrilled to share how we’re bringing the facility of databases and Cloth collectively to kind a really converged information platform—one which unifies transactional, operational, and analytical information beneath a single, constant structure. I’ll additionally spotlight how we’ve enhanced Cloth that will help you remodel information into the semantic information AI wants to grasp what you are promoting, powered by Cloth IQ and Energy BI’s industry-leading semantic mannequin know-how.

Introducing the Database Hub in Microsoft Cloth

Databases sit on the coronary heart of the enterprise information property—a system of file powering purposes, transactions, and mission‑vital insights. But as organizations scale throughout cloud, on‑premises, and edge environments, database estates have turn out to be more and more fragmented and remoted. As AI locations even higher calls for on information estates, unifying databases beneath a single entry level and management aircraft has turn out to be important.

To handle this problem, Cloth is increasing its function because the central entry level for enterprise information with the Database Hub in Cloth, now out there in early entry. Database Hub in Cloth gives a unified database administration expertise that brings collectively databases throughout edge, cloud, and Cloth right into a single, coherent view. Groups now have one place to discover, observe, govern, and optimize their total database property—together with Azure SQL, Azure Cosmos DB, Azure Database for PostgreSQL, SQL Server (enabled by Azure Arc), Azure Database for MySQL, and Cloth Databases—with out altering how every service is deployed.

Constructed for scale, the Database Hub in Cloth introduces an agent‑assisted, human-in-the loop strategy to database administration. With built-in observability, delegated governance, and Microsoft Copilot-powered insights, groups can deploy clever brokers to constantly motive over property‑huge alerts and floor what modified, clarify why it issues, and information groups towards what to do subsequent. The result’s an easier, extra assured solution to handle databases at scale. Over time, this mannequin permits database estates to turn out to be extra proactive, resilient, and clever, laying the inspiration for higher autonomy, whereas holding people firmly answerable for objectives, boundaries, and belief.

Past unified database administration, we’re additionally introducing financial savings plan for databases, a brand new solution to save by as much as 35% in comparison with pay-as-you go pricing on choose companies.*

Bringing databases collectively beneath a single administration layer is a vital step as you put together your estates for AI at scale. Nevertheless it’s not the tip of the journey. The problem shifts from the place information lives to how information is known, linked, and activated throughout the enterprise.

Getting your information property prepared for AI with Cloth

As organizations transfer from conventional purposes to AI‑powered, multi‑agent techniques, the benefit is shifting away from the particular mannequin you deploy. It now lies within the intelligence and context that enable brokers to grasp how what you are promoting is run, the state of what you are promoting, and your institutional information to assist take significant motion.

That is the problem Microsoft IQ is designed to deal with. In contrast to level options available on the market immediately, Microsoft IQ gives an intelligence layer that delivers shared, enterprise-grade enterprise context to each agent. That context is constructed from three complementary sources: productiveness alerts from Work IQ, institutional information from Foundry IQ, and stay enterprise information from Cloth IQ.

Nevertheless, just like the database layer, whereas the IQ context layer is a vital a part of a profitable, and wholesome AI basis, it’s not the complete story. Constructing an entire AI-ready information basis requires investing in 4 core steps:

1. Unifying your information property to remove silos and cut back architectural complexity.
2. Processing and harmonizing information so it turns into AI-ready, clear, linked, and structured for each operational and analytical use.
3. Curating semantic that means to present brokers contextual understanding, enabling them to interpret information the way in which your groups already do. That is the place Microsoft IQ comes into play.
4. Empowering AI brokers to behave, making use of that context to automate workflows, speed up choices, and remodel operations finish‑to‑finish.

Unifying your information property with Microsoft OneLake

Each AI initiative begins with the identical elementary problem: understanding the place your information lives and find out how to deliver it collectively. Microsoft OneLake was constructed to resolve that downside by unifying information throughout clouds, on-premises environments, and third-party platforms right into a single logical information lake with out pointless extracting, remodeling, and loading (ETL), fragmentation, or duplicated copies.

Connecting to extra sources than ever earlier than

At this time, we’re increasing Mirroring in Cloth to assist much more techniques our prospects depend on. Mirroring for SharePoint lists and Dremio are actually in preview with Azure Monitor coming quickly, whereas mirroring for Oracle and SAP Datasphere are typically out there—all of which can be found as a part of the core mirroring capabilities. We’re additionally introducing prolonged capabilities in mirroring designed that will help you operationalize mirrored sources at scale, together with Change Knowledge Feed (CDF) and the flexibility to create views on high of mirrored information, beginning with Snowflake. Prolonged capabilities for mirroring will likely be supplied as a paid choice.

Shortcut transformations are additionally now typically out there, permitting information to be formed robotically because it connects to or strikes inside OneLake. You may convert codecs comparable to Excel to Delta tables, now in preview, and apply AI-powered transformations.

Moreover, we’re persevering with to spend money on open interoperability, guaranteeing OneLake works seamlessly with the platforms organizations already use. We’re excited to announce the flexibility to natively learn from OneLake via Azure Databricks Unity Catalog is now in public preview. We additionally not too long ago introduced the common availability of our interoperability with Snowflake.

I’m additionally excited to share that Auger, a quickly rising provide chain platform designed to deliver intelligence and automation to world operations, has constructed its platform on Cloth, with all information saved natively in OneLake. This structure permits Auger prospects to seamlessly entry their operations information via OneLake shortcuts inside their very own Cloth environments and use the complete energy of the platform together with Energy BI, Cloth information brokers, and extra. Study extra in my weblog, co-authored with Auger Chief Government Officer Dave Clark.

Shield your information with OneLake safety, now typically out there

Safety and governance stay foundational to OneLake. I’m thrilled to announce OneLake safety will likely be typically out there within the coming weeks, enabling information homeowners to outline roles, implement row- and column-level controls, and handle permissions via a single unified mannequin that follows the information.

To study extra about these bulletins, learn the OneLake weblog and the Cloth Knowledge Manufacturing unit weblog.

Processing and harmonizing information with Cloth analytics

AI brokers are solely as dependable as the information you feed them. Earlier than information can practice or floor an agent, it should be built-in, cleaned, and structured, so the agent operates from constant, trusted info. With industry-leading engines in Cloth like Spark, T-SQL, KQL, and Evaluation Providers, we are able to equip information groups to do precisely that.

Now, we’re increasing these capabilities with the introduction of Runtime 2.0 in preview, purpose-built for large-scale information computation. It incorporates Apache Spark 4.x, Delta Lake 4.x, Scala 2.13, and Azure Linux Mariner 3.0 to energy superior enterprise workloads. Materialized lake views are additionally now typically out there, simplifying medallion structure implementation in Spark SQL and PySpark and enabling all the time up-to-date pipelines with no guide orchestration. As well as, a brand new agentic Copilot expertise in notebooks delivers deeper context consciousness, reasoning over your workspace, and producing code with higher velocity and precision.

For real-time situations, we’re launching Maps in Cloth into common availability. Maps add geospatial context to your brokers and operations by turning giant volumes of location-based information into interactive, real-time visible insights.

For a complete overview of those bulletins and way more, learn the Cloth Analytics weblog and the Cloth Actual-Time Intelligence weblog.

Creating semantic that means with Cloth IQ

Making ready uncooked information for AI is important. The following step is remodeling that information into significant, unified enterprise context. That’s the place Cloth IQ is available in.

Cloth IQ unifies analytical information and operational information, together with telemetry, time collection, graph, and geospatial information, inside a shared semantic framework of enterprise entities, relationships, properties, guidelines, and actions. As a substitute of considering when it comes to tables and schemas, your groups and brokers can function on this framework, or ontology, aligned to how the enterprise really runs.

Cloth IQ ontologies will quickly turn out to be accessible via an MCP server in preview, enabling brokers to find, perceive, and act on this semantic layer. Ontologies can even function context sources for maps and shortly in operations brokers in Cloth, extending shared enterprise context immediately into operational decision-making and execution.

We’re additionally excited to announce planning in Cloth IQ, a brand new enterprise planning functionality that allows organizations to create plans, budgets, forecasts, and state of affairs fashions immediately on high of Cloth’s semantic fashions. By complementing Cloth IQ’s ontologies with built-in planning, you get an entire, contextual view of your historic, real-time, and ahead planning information. This enables customers and brokers to shortly reply what has occurred, what is going on, and what ought to occur all from a single supply. See this in motion:

Lastly, we not too long ago introduced a strategic partnership with NVIDIA to energy the subsequent technology of Bodily AI by integrating Actual-Time Intelligence and Cloth IQ with NVIDIA Omniverse libraries. The mixed platform unifies actual‑time operational information, enterprise semantics, and bodily simulation to allow organizations to optimize their bodily operations in situations like clever digital twins, predictive upkeep, autonomous logistics, and power optimization.

To study extra about all of our associate bulletins, learn the Cloth ISV weblog and the planning in Cloth IQ weblog.

Enhancing the underlying Cloth IQ know-how

Powering a lot of Cloth IQ’s wealthy expertise is a mix of Energy BI’s industry-leading, wealthy semantic mannequin know-how and graph in Cloth, our extremely scalable graph database. Already delivering insights to greater than 35 million lively customers, semantic fashions present the perfect basis for coaching brokers via Cloth IQ. Now, with the overall availability of Direct Lake on OneLake, your tables will be learn immediately from OneLake with native safety enforcement, richer cross-item modeling, and import-class efficiency with out information motion or refresh.

I’m additionally excited to share that graph in Cloth will likely be typically out there within the coming weeks, enabling groups to visualise and question complicated relationships throughout prospects, companions, and provide chains.

To study extra, take a look at the Cloth IQ weblog and the Energy BI weblog.

Empowering brokers to behave with Cloth information and operations brokers

Frontier organizations are shifting past general-purpose assistants and as a substitute, adopting multi-agent techniques composed of specialised brokers. These brokers are every grounded on particular information and reusable throughout totally different techniques, permitting you to ship extra correct, accelerated, and scalable outcomes.

To assist your multi-agent techniques, Cloth comes with built-in agent creation capabilities with Cloth information brokers and operations brokers. I’m excited to share that Cloth information brokers are actually typically out there. Cloth information brokers will be regarded as digital analysts, aligned to particular area information to assist deeper evaluation and ship insights. Operations brokers complement them by monitoring real-time information, detecting patterns, and taking proactive motion.

Try a fast demo of operations brokers in Cloth:

These brokers can be utilized throughout Cloth or as foundational information sources in main AI instruments like Microsoft Foundry, Copilot Studio and even Microsoft 365 Copilot. To study extra about our AI bulletins, take a look at the Cloth analytics weblog protecting information brokers and the Cloth IQ weblog protecting operations brokers.

Constructing mission-critical purposes with developer experiences in Cloth

Builders constructing the subsequent technology of AI purposes want a complete, cost-effective information platform that’s already built-in together with your current instruments and workflows. At this time, we’re increasing Cloth’s developer tooling to satisfy that demand.

First, Cloth Mannequin Context Protocol (MCP) is advancing with two main milestones. Cloth native MCP is now typically out there, offering an open-source native server that connects AI coding assistants comparable to GitHub Copilot on to Cloth. Alongside this, we’re introducing the general public preview of Cloth distant MCP, a safe, cloud‑hosted execution engine that allows AI brokers and automation instruments to carry out authenticated actions in Cloth.

We’re additionally enhancing our Git integration with selective branching, permitting builders to department out for a selected characteristic and pull solely the gadgets they want. You additionally get improved change comparisons to extra simply evaluation latest updates, and new folder relationships which present how characteristic workspaces connect with supply workspaces.

We’re additionally launching two open-source initiatives to assist groups transfer quicker with Cloth: Agent Expertise for Cloth and Cloth Jumpstart. Agent Expertise for Cloth is an open-source set of purpose-built plugins that allow you to use pure language within the GitHub Copilot terminal to harness the complete energy of Microsoft Cloth. Moreover, Cloth Jumpstart is designed that will help you get off the bottom with detailed steerage, reference architectures, and single‑click on deployments for pattern datasets, notebooks, pipelines, and studies.

Lastly, we’re asserting that the Cloth Extensibility Toolkit (FET), an evolution of the Workload Growth Equipment (WDK), is now typically out there. Together with this launch, we’re enabling assist for full CI/CD, variable library, and a brand new administration expertise within the Admin portal.

Migrating your current Azure service to Cloth

As Cloth continues to develop in performance, we’re additionally simplifying the migration from different Azure companies. Along with our current Synapse tooling, we’re bringing new migration assistants for Azure Knowledge Manufacturing unit, Azure Synapse Analytics, and Azure SQL in public preview.

The brand new Cloth migration assistant for Azure Knowledge Manufacturing unit and Synapse Analytics helps transfer your current pipelines and artifacts like Spark swimming pools and notebooks into Cloth with minimal disruption. It’s designed to assist incremental modernization, permitting groups to guage, convert, and optimize pipelines as they transition to Cloth. The migration assistant for SQL databases helps transfer SQL Server into Cloth by importing schemas via DACPACs, figuring out and resolving compatibility points with AI help, and guiding groups via evaluation and information copy workflows for a smoother cutover.

See extra Cloth innovation

Along with the bulletins above, we’re additionally rolling out a broad set of Cloth improvements throughout the platform. For a deeper have a look at the updates and what’s new this month, go to the Cloth March 2026 Characteristic abstract weblog, the Energy BI March 2026 characteristic abstract weblog, and the newest posts on the Cloth Updates channel.

Discover extra assets for Microsoft Cloth