Microsoft Fabric Expands with AI Integration and Database Support to Streamline Enterprise Data Management

Microsoft Fabric upgrades aim for better integration of data and AI agents

Two years after the debut of Microsoft's "end-to-end, unified analytics platform," Fabric, the company on Monday rolled out new capabilities at its Build 2025 conference. Also: You can try Microsoft's free AI skills training for two more weeks, and I recommend you do The innovations show a maturation of Microsoft's database, reporting, and AI functions as the individual offerings become more integrated. In broad strokes, the main new capabilities include: The digital twin builder, currently in public preview, aims to overcome hurdles in building digital twins such as "fragmented data sources, inconsistent data quality, and challenges in governance and security," said Microsoft. Also: Deploying digital twins: 7 challenges businesses can face and how to navigate them Digital twins are an increasingly popular way to simulate entities in the world, from human organs to aircraft, in order to project drug effects on organs or predict parts failure in heavy equipment. The builder tool is composed of four capabilities: modeling, mapping, relationships, and extensions. Modeling includes having shared structures that replicate things in the real world. Mapping ensures a correspondence between real-world entities and the digital replicas. Those relationships are then broadened out into "semantic relationships and dependencies" via the relationships function. And the extensions feature allows one to apply analytics, visualization, and AI to the twins. Also: The 5 stages of digital twin development An early customer for the technology is US rail-freight giant CSX Corporation of Jacksonville, Florida. The twin builder's ability to make an "ontology" that maps between the real world and the simulated world was used to unify "critical metadata" about locomotives and train lines, "such as locomotive specifications (cargo type, weight, etc.) and train line attributes (starting point, endpoints, stations, etc.)," the company said in a prepared statement. The Fabric with Copilot function is meant to "thoughtfully" integrate gen AI into the platform, said Microsoft. The tool makes it possible to do things such as "creating data flows, generating code, or even asking questions to better understand data in a Power BI report." Also: With Copilot Studio's new skill, your AI agent can use websites and apps just like you do The agent service, called Fabric Data Agents, which will soon be in public preview, is meant to connect to custom AI agents that are built in Copilot Studio. The Copilot Studio agent draws data from OneLake and can also set in motion workflows, said Microsoft, such as sending an email, in order to "automate processes, making it easier for users to interact with data, and streamline tasks without leaving the chat experience." Get the morning's top stories in your inbox each day with our Tech Today newsletter.

Microsoft stitches transactional databases to Fabric

SQL Server and Cosmos DB added to data lake platform as lure for building AI features into transactional systems Microsoft is throwing more transactional database systems into its Fabric analytics and data lake environment in expectation the proximity will help users that are adding AI to their systems. During its Build conference this week, the Redmond software and cloud biz said it was adding transactional document database Cosmos DB and its relational workhorse SQL Server to Fabric, the analytics and data lake platform first announced in June 2023. Adding Cosmos DB's global secondary index to Fabric, for example, would remove the need to scan all the operational data in an Azure Cosmos DB database, Microsoft said. This is intended to enable faster queries and minimize latency while also helping to make sure that queries do not negatively impact transactional performance, the vendor argued. Arun Ulag, corporate vice president for Azure data, told The Register the idea is to let customers bring AI and analytics workloads closer to their transactional data as the two would share the same underlying file format, Apache Parquet, in the data lake environment, which Microsoft calls OneLake and uses the open source Delta Lake format. "Cosmos DB is a great place to store your entire product catalog, for example, and with customers browsing around your website, you want to make recommendations. Anything built on Fabric, by default, all of the data, whether it's SQL Server or Cosmos DB or a data warehouse or data lake, is sitting on OneLake," he said. "Everything is in the open source, Apache Parquet, Delta Lake format, which means if you're building a machine learning model, the data is just there and always current. You don't need to build copies. You don't need to shuttle data around. You can build your machine learning models directly on top of OneLake." Aaron Rosenbaum, Gartner senior director, data management and analytics, said the move was part of a continuing trend of making integration simple and automated between different parts of the data management infrastructure. "The replication is announced as 'near real time,' enabling reporting on operational data in PowerBI join directly against other assets in Fabric. CosmosDB a key component of many GenAI applications built on Azure. It allows for the real-time interaction support and directly supports vector indexes. These vector embeddings carry over to the Fabric copy and can be utilized on analytics in Fabric," he told us. Keen readers might have noticed Microsoft gave developers looking for a document database another option earlier this year, by creating open-source extensions to PostgreSQL, commonly provided as a service by cloud providers. Ulag said Microsoft's relational database of choice remains SQL Server and the document database of choice is still Cosmos DB yet. "We've made massive investments in PostgreSQL, so from our perspective, we want to give customers a choice. If PostgreSQL is your database of choice, and on top of that, you want to run a document database, fantastic, we have a PostgreSQL extension that just does that."

Why Microsoft Fabric has already been adopted by 70% of the Fortune 500 -- and what's next

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Microsoft is bringing even more database options into the Microsoft Fabric fold, alongside a series of initiatives that aim to help tackle enterprise data complexity. For literally generations of databases, compute and storage were always tightly coupled. That caused all kinds of scalability and data silo issues for enterprises. In 2023, Microsoft Fabric was first introduced as a strategy to help overcome that challenge. The basic idea behind Microsoft Fabric is to be a common data layer across Microsoft's data and analytics tools. In November 2024, Microsoft Fabric expanded with support for the Azure SQL transactional database platform. Microsoft, just like its rivals at Google at Amazon, has a lot of different database platforms. While Azure SQL is widely used, when it comes to AI there is another more influential database platform and that's CosmosDB. At the Build 2025 conference today, Microsoft is announcing that CosmosDB is finally coming to Microsoft Fabric. CosmosDB is among the most critical databases in use today for AI as it is the database that is at the foundation for OpenAI's ChatGPT service. CosmosDB is also getting a boost via integration with Azure AI Foundry, giving more direct access for agentic AI to data. There are also a series of additional data updates including support for Microsoft Copilot in the PowerBI business intelligence platform. SQL Server 2025 database is being previewed and the DiskANN (Disk Approximate Nearest Neighbor) vector index is being open sourced. These innovations directly address the integration complexity that plagues enterprise data teams when building AI applications. A key focus is to eliminate the data fragmentation that hampers enterprise AI initiatives. "When I talk to customers, the message I consistently get is, please unify, I'm Chief Information Officer, I don't want to be the Chief Integration Officer helping translate AI into my competitive advantage," Arun Ulag, Corporate Vice President for Azure Data at Microsoft, told VentureBeat. Fabric accelerates enterprise AI by eliminating data silos Microsoft Fabric, the company's unified data platform, continues its rapid growth trajectory by bringing previously separate products together in a cohesive ecosystem. "We're bringing all of our products together and unifying them into a single product, which is Microsoft Fabric," Ulag said. "In some ways, you can think about Fabric as almost like what we did with Office 30 years ago." This strategy has clearly resonated with enterprises. Ulag said that Microsoft Fabric now has over 21,000 organizations as paying customers worldwide, including 70% of the Fortune 500. "It's growing very, very quickly," he said. CosmosDB in Fabric eliminates NoSQL infrastructure overhead The headline addition to Fabric is CosmosDB, Microsoft's NoSQL document database that powers many high-profile AI applications. "CosmosDB is, by far, often becoming the database of choice for the world's AI workloads," Ulag said. "ChatGPT itself is built on CosmosDB... Walmart's e-commerce store runs on CosmosDB as well." By bringing CosmosDB into Fabric, Microsoft enables organizations to deploy NoSQL databases without managing complex infrastructure. A key challenge of having a disaggregated compute and storage approach is maintaining performance without latency. Microsoft has taken very specific technical steps to maintain performance through an innovative caching system. "Inside Fabric, we maintain a highly performant cache, which handles all the fast updates that CosmosDB does," Ulag explained. "We have a very fast synchronization mechanism that is completely transparent to the customer, where the data is replicated in near real-time into OneLake." This approach delivers millisecond response times required for AI applications while eliminating infrastructure management tasks. Why open source data formats are key to Fabric's success While Microsoft connects all its data products through the Fabric strategy, OneLake technology actually stores the data. There is tremendous complexity in having a unified data lake that handles multiple different data types and formats from SQL, NoSQL and unstructured data. It's a challenge that Microsoft is solving with an open source approach. "Microsoft has completely embraced open source data formats, so everything in Fabric, regardless of whether which workload it is, by default, is always in Apache Parquet and Delta Lake," Ulag said."It's really a unified product, with the unified architecture and a unified business model, with all of the data sitting in a global SaaS data lake, which is OneLake in open source data formats." This optimization means all Fabric services, from SQL to Power BI to CosmosDB, can access the same underlying data without conversion or duplication, eliminating the traditional performance penalty associated with open formats. DiskANN open source release brings enterprise-grade vector search to all Microsoft isn't just using open source for data formats, it's also contributing its own code too. At Build, Microsoft is announcing that it is open sourcing the DiskANN vector search technology. Microsoft's decision to open source DiskANN represents a significant contribution to the AI ecosystem, making enterprise-grade vector search capabilities available to all developers. "We have a very, very strong vector capability called DiskANN, it was originally created in Microsoft Research, and it's used in Bing... built into CosmosDB and built into Fabric," said Ulag. DiskANN implements approximate nearest neighbor (ANN) search algorithms optimized for disk-based operations, making it ideal for large-scale vector databases that exceed memory limitations. By open sourcing DiskANN, Microsoft enables developers to implement the same high-performance vector search used by ChatGPT and other leading AI applications. This helps address one of the key challenges in building retrieval-augmented generation (RAG) systems, where finding semantically similar content quickly is essential for grounding AI responses in enterprise data. "We're allowing everybody to be able to get the benefits of the vector store that we're using internally," Ulag said. Why it matters for enterprise data leaders For enterprises leading in AI adoption, these announcements enable more sophisticated applications that seamlessly integrate multiple data types. The complexity and the challenges of dealing with data silos aren't just about different locations but different formats too. The continued evolution of Microsoft Fabric directly addresses that concern in a way that no other hyperscaler is doing today. The focus and commitment to open source standards at the core is also important for enterprises as it removes some lock-in risk that would be present if the data was stuck in proprietary formats. As enterprises increasingly compete on AI capabilities, Microsoft's unified approach removes a significant barrier to innovation. Organizations that embrace this integration can shift their focus from maintaining complex data pipelines to creating AI applications that deliver tangible business value -- potentially outpacing competitors still struggling with fragmented architectures.

Microsoft expands Fabric and Azure data portfolio to simplify AI development - SiliconANGLE

Microsoft expands Fabric and Azure data portfolio to simplify AI development Microsoft Corp. today is announcing at its annual Build conference a broad range of enhancements across its data platforms aimed at simplifying artificial intelligence application development. The updates span Microsoft Fabric, Azure Cosmos DB, SQL Server, Power BI, PostgreSQL and integrations with Databricks Inc.'s and SAP SE's services on the Azure cloud. The aim is to offer developers a more cohesive and efficient toolkit for building intelligent applications. Microsoft Fabric, a data platform intended to unify all data and analytics services, now includes support for semistructured data through the preview of Azure Cosmos DB, a NoSQL and vector database. This allows developers to manage unstructured and semistructured data types such as documents, text and emails for analytics. Cosmos DB is known for its scalability, reliability and support of both SQL and NoSQL. Data is automatically accessible in OneLake, the unified data lake storage system built into Microsoft Fabric. That enables real-time analytics scenarios like sentiment analysis in chat applications. Fabric Real-Time Intelligence for streaming data now includes a digital twin builder in preview. This no-code/low-code tool helps developers model and manage virtual replicas of physical and logical entities, Microsoft said. It's designed for what-if analysis and process modeling in scenarios such as manufacturing, logistics and customer profiling. Microsoft is also expanding the use of Azure Cosmos DB within the Azure AI Foundry unified AI development platform to support AI agents that remember and resume prior user interactions. This thread storage capability, now generally available, allows AI agents to maintain contextual continuity in conversations, which is a critical component for natural user experiences. A new full-screen Copilot in Power BI enables users to query data conversationally. Copilot can search across multiple reports and semantic models, integrating directly into Microsoft Teams and Microsoft 365. Fabric data agents created in Copilot Studio can now be embedded in Microsoft 365 and Teams, automating routine tasks and enabling deeper interaction with enterprise data. Keeping the 35-year-old SQL Server relevant in the AI age, the 2025 edition, now in public preview, has been expanded to include vector database functionality. It supports AI applications through native vector search, local or cloud-based AI model interfaces and integration with frameworks such as LangChain for large language models and Semantic Kernel for AI agents. It also supports real-time data mirroring into Fabric and deployment through Azure Arc. PostgreSQL on Azure is also getting significant upgrades to help developers extract more meaningful context from relational data. A new VS Code extension, integrated with GitHub Copilot, streamlines database development with AI assistance for query writing and schema design. DiskANN, a high-performance vector indexing algorithm, is now generally available in Azure Database for PostgreSQL, offering a faster alternative to pgvector. Semantic operators powered by large language models are also in preview, enabling GenAI reasoning directly within PostgreSQL. Microsoft also plans to tighten its integration with SAP's Business Data Cloud and SAP Databricks on Azure early this summer. The platform will allow developers to build AI applications on top of SAP business data using Microsoft's first-party Databricks service. This setup offers scalability and security while maintaining tight integration with Azure. Mirroring capabilities now allow Azure Databricks Unity Catalog tables to be synced in real-time with OneLake. Developers can reference Databricks tables across services with minimal setup, streamlining data access and management across cloud environments. Azure AI Foundry agents can now execute Databricks jobs and use Databricks' AI/BI Genie conversational interface for data retrieval and contextual response generation.