Microsoft Fabric Integrates Transactional Databases to Boost Enterprise AI Development

Build Autonomous SQL Databases in Microsoft Fabric

Microsoft Fabric is ushering in a new era of database management through its innovative autonomous SQL databases. These innovative databases are designed to streamline your management tasks while significantly enhancing application development capabilities. By seamlessly integrating operational and analytical data across various cloud environments, Microsoft Fabric is set to transform the way you handle and interact with data. If you've ever found yourself tangled in the web of manual database configurations, Microsoft Fabric's autonomous SQL databases might just be the breath of fresh air you need. These databases are not just about reducing the hassle; they're about transforming how we interact with data across multiple clouds, making it easier and more intuitive. The seamless integration of operational and analytical data promises to transform your workflow, allowing you to focus on what truly matters: building innovative applications. But what makes these databases truly stand out is their ability to adapt and optimize without constant human intervention. Picture a system that automatically scales, tunes, and secures itself, all while making sure high availability through multiple zones. It's like having a reliable co-pilot who handles the technical turbulence, so you can enjoy the journey of creativity and innovation. And with built-in AI capabilities, querying and troubleshooting become as intuitive as having a conversation. At the core of Microsoft Fabric lie its autonomous database features, which represent a significant leap forward in database technology: These autonomous databases automatically adjust their scale and performance, drastically reducing the need for manual intervention. They come equipped with robust security measures and receive regular updates to ensure your data remains protected against evolving threats. High availability is guaranteed through the implementation of multiple availability zones, making sure your applications remain functional even in the face of unexpected failures or outages. Setting up SQL databases has never been more straightforward. Microsoft Fabric offers an accelerated setup process, allowing you to get started without unnecessary delays. The platform provides seamless integration with APIs, making sure smooth data interaction across your entire technology stack. Furthermore, the familiar SQL server experience allows you to use your existing skills effectively, reducing the learning curve and increasing productivity. Here are additional guides from our expansive article library that you may find useful on databases. Microsoft Fabric fully supports CI/CD (Continuous Integration/Continuous Deployment) pipelines, making it compatible with popular development tools such as Azure DevOps and GitHub. This integration significantly simplifies your development workflow, allowing you to focus on building robust applications without getting bogged down by the complexities of database management. The platform's support for modern development practices enables faster iteration and more efficient collaboration among development teams. Data replication becomes highly efficient with the conversion to Delta Parquet format in OneLake, making sure your data is both easily accessible and manageable. Intelligent load balancing optimizes both operational and analytical processes, improving overall system performance. Data shortcuts enable data references without unnecessary duplication, significantly enhancing accessibility and reducing storage costs. Microsoft Fabric incorporates state-of-the-art AI technologies to improve data interaction and analysis: These AI-powered features allow for more natural and effective data queries, making it easier to derive meaningful insights from your data. The integration with Azure AI services offers advanced analytical capabilities, allowing you to uncover hidden patterns and trends in your datasets. Security and compliance are fundamental to Microsoft Fabric's design philosophy. Identity and access management are handled through Microsoft Intra, making sure secure and controlled data access. The platform's integration with Microsoft Purview enhances security further, providing comprehensive compliance management tools to help you meet regulatory requirements and industry standards. Microsoft Fabric places a strong emphasis on optimizing the developer experience. The platform offers: This developer-centric approach ensures efficient application building and deployment, allowing you to use the full potential of autonomous databases without getting caught up in complex management tasks. Microsoft Fabric's autonomous SQL databases are currently available in public preview, with a free trial option for those interested in exploring their capabilities. This availability provides an excellent opportunity for you to evaluate the impact of these advanced databases on your application development processes and overall database management strategy. Microsoft Fabric's autonomous SQL databases represent a comprehensive solution for modern database management. By integrating advanced features, seamless development tools, and robust security measures, these databases empower you to focus on innovation and application development. As data continues to play an increasingly critical role in business operations and decision-making, Microsoft Fabric stands poised to become an indispensable tool in your technology arsenal, offering the scalability, security, and efficiency needed to thrive in today's data-driven landscape.

SQL Server Now Natively Integrates into Microsoft Fabric

The adoption of Microsoft Fabric includes 70% of the Fortune 500, reinforcing its dominance in enterprise data management. In an exciting announcement, Microsoft revealed that SQL Server is now integrated into Microsoft Fabric databases, combining operational and analytical databases in one unified platform. "It's a unified platform for all operational and analytical data," added Nadella. As mentioned at the event, Microsoft is investing in data innovation across this platform. SQL Server 2025, now in preview, introduces itself as an enterprise AI-ready database designed to operate seamlessly from ground to cloud. This latest version integrates AI capabilities, simplifying AI development and pattern recognition with secure performance and intuitive vector capabilities, all while using the familiar T-SQL language. Source: Microsoft Additionally, building on its reputation for best-in-class security and performance, the new release amplifies automation for threat management and addresses potential vulnerabilities through Microsoft's advanced management capabilities while fully integrated with Azure, offering upgraded cloud security and agility. Earlier this year at Microsoft Build, the tech giant launched real-time intelligence in its AI-powered analytics platform, Microsoft Fabric. The new feature offers a comprehensive SaaS solution, enabling customers to quickly analyse and act on large-scale, time-sensitive data for improved business decision-making. It integrates synapse real-time analytics and data activator. Traditionally, constructing real-time solutions has been complex and resource intensive. However, according to Microsoft CEO Satya Nadella, this new feature claims to simplify this process by offering a "unified platform" that leverages Microsoft's Azure streaming and big data technologies. This ensures scalability, reliability, and ease of use, catering to users of all skill levels.

Microsoft supercharges Fabric with new data tools to accelerate enterprise AI workflows

The move -- a significant departure from the long-standing reliance on OpenAI -- promises enhanced flexibility to developers, but we all know AI is just 'garbage in and garbage out' without a solid data foundation. To this end, Microsoft also announced a series of updates for Fabric, its end-to-end SaaS data platform. According to Arun Ulag, the corporate VP of Azure data, the biggest development is the integration of transactional databases, which will transform Fabric into a truly unified, open data platform bringing all the necessary technologies together in one place to build next-gen AI applications, including advanced agents. Other notable capabilities, some of which are being previewed while others are generally available, touch on different aspects of how Fabric operates, including data connectivity, workload performance, scalability, security and governance. "We are relatively early in the AI journey... There are many more customers, business users, and developers that can take advantage of these technologies. And as they take advantage of these tools, we have to evolve them. We have to drive costs further down and make sure that we further accelerate business value. Ultimately, all of this should translate into higher GDP growth for countries and stronger business outcomes for customers," Ulag said in an interview with VentureBeat. Transactional database integration for fast-tracked AI development Microsoft launched Fabric last year as a SaaS-based data and analytics platform to bring its innovations across the data stack in one place. The unified offering leveraged several tools the company built over the years, including SQL Server, Excel, Power BI and Azure Synapse, and provided teams with an end-to-end experience to connect, manage and analyze large structured and unstructured data assets. At the core, Fabric is underpinned by an open lakehouse architecture called OneLake. It serves as a central, multi-cloud repository that supports various open data formats (Apache Parquet, Delta Lake and Iceberg) and the downstream analytical workloads. In the last few months, both Fabric and OneLake have received several improvements, including Real-Time Intelligence - which now becomes generally available - for analyzing streaming logs, IoT and telemetry as well as tools for migrating data from other data environments. However, running analytical workloads to identify trends and patterns is just one piece of the puzzle. AI is the real deal today, and for that, the users need to go beyond aggregated, historical data. To help with this, Microsoft has announced Fabric Databases, which will see different transactional databases plug into OneLake, allowing users to access both live data from transactional systems (think individual purchase or login events) and bulk analytical data through one unified layer. The company is starting with the integration of its own Azure SQL database and will follow up with other transactional databases including including Cosmos DB (its NoSQL document database behind ChatGPT), PostgreSQL, MongoDB and Cassandra. It hopes the move will save developers from complex database integrations and enable them to power next-gen AI apps, managing billions of interactions daily. "Built-in vector search, RAG support, and Azure AI integration simplify AI app development, and your data is instantly available in OneLake for advanced analytics. Developers can even use Copilot in Fabric to translate natural language queries into SQL and get inline code completion alongside code fixes and explanations," Ulag noted in a blog post today. OneLake catalog, new AI features and more In addition to transactional databases, Fabric is getting a new OneLake catalog to make it easier for teams to explore, manage and govern their entire Fabric data estate, no matter where the information has come from, as well as several AI capabilities to accelerate workflows. The catalog, as Ulag wrote in the blog, carries two main tabs: Explore and Govern. The former is generally available and will help teams discover and manage their trusted data. Meanwhile, the Govern tab, aimed at providing data owners with valuable insights, tools and recommendations for governing their data, is in preview at this stage. These features will ensure that the teams are aware of what's going on across the platform, without running into any surprises. On the AI front, Microsoft is now previewing AI functions in Fabric notebooks, providing a simplified API for common AI text enrichments like summarization, translation, sentiment analysis, and more. The company is also enhancing AI skills (preview), which allow users to build agents that can be pointed to query any data across multiple systems via natural language. Ulag wrote AI skills now have an improved conversational experience. Plus, they can now connect to semantic models and Eventhouse KQL databases, going beyond lakehouse and data warehouse tables, mirrored DB and shortcut data. Among other notable updates, Microsoft announced the general availability of API for GraphQL to allow efficient querying of multiple data sources using the widely adopted GraphQL technology; support for new events and simplified dashboard sharing in Real-Time Intelligence; and preview of open mirroring, a feature that allows any application or data provider to write data changes directly into a mirrored database within Fabric. It also confirmed the general availability of Azure SQL DB mirroring and the preview of SQL managed instance mirroring. Finally, Fabric users will also get workspace monitoring and surge protection in preview. The former will provide detailed diagnostic logs for troubleshooting performance issues, capacity performance and data downtime, while the latter will prevent background jobs from starting after a set threshold.

Microsoft Fabric gets enhanced AI development and data integration features - SiliconANGLE

Microsoft Fabric gets enhanced AI development and data integration features Microsoft Fabric is getting new tools and capabilities to streamline artificial intelligence application development, enhance data integration and improve security in a series of announcements at Microsoft Corp.'s Ignite conference today. Fabric is an integrated analytics platform that unifies data integration, engineering, warehousing, science and business intelligence on top of a unified data lake. The updates are aimed at improving developer, analyst and data scientist productivity and simplifying access to data through a catalog. New Fabric Databases, now in preview, are intended to provide simpler database provisioning with autonomous functions. The first available volume, SQL Databases in Fabric, allows data to be automatically replicated to Fabric's integrated OneLake data lake for immediate use by Fabric's analytical tools. A feature native vector search combined with Azure AI embedding models supports advanced artificial intelligence functions like retrieval-augmented generation. Native vector search is a technique in which data is represented as high-dimensional vectors, and search is performed by finding items whose vectors are closest to a query vector, rather than necessarily being an exact match. Vector data is a critical element in machine learning model training and semantic search. The auto-optimizing and auto-scaling databases provide faster application performance through intelligent indexing, Microsoft said. Developers can leverage a Fabric Copilot to translate natural language queries into SQL as well as complete code and deliver in-line explanations. Integration with GitHub and Visual Studio Code, a lightweight, open-source code editor developed by Microsoft, support continuous integration and deployment and simplify database updates and source control. A common data estate ensures consistent governance policies. Microsoft is also expanding AI capabilities within Fabric to make generative AI more accessible. AI Functions in Fabric is a new feature that allows users to perform text-related tasks such as summarization, translation and sentiment analysis with minimal coding. Simplified application programming interfaces reduce AI enrichment complexity. Azure AI Agent Service Integration enables simplified connection to enterprise data sources, including SharePoint, to automate tasks. A new Open Mirroring capability, now in preview, allows applications and data providers to more easily bring external data estates into OneLake. Mirroring simplifies data replication by creating an exact copy of data from one system to another in a way that ensures that both the primary and secondary systems have identical data at any given point in time. The OneLake Catalog, now generally available, provides a unified platform for exploring, managing and governing Microsoft Fabric data. It provides a central interface for discovering data, including filters for domains, owners and tags. New features coming next year will help with data quality, labeling and compliance with actionable recommendations.

Microsoft brings transactional databases to Fabric to boost AI agents

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More For years, enterprise companies have been plagued by data silos separating transactional systems from analytical tools -- a divide that has hampered AI applications, slowed real-time decision-making, and driven up costs with complex integrations. Today at its Ignite conference, Microsoft announced a major step toward breaking this cycle. The tech giant revealed that Azure SQL, its flagship transactional database, is now integrated into Fabric, Microsoft's unified data platform. This integration allows enterprises to combine real-time operational and other historical data into a single, AI-ready data later called OneLake. This announcement represents a critical evolution of Microsoft Fabric, its end-to-end data platform, which also includes new capabilities like real-time intelligence and the general availability of the OneLake catalog (see our full coverage of the Microsoft Ignite data announcements here). Together, these updates aim to address the growing demand for accessible, high-quality data in enterprise AI workflows. Until now, companies have struggled to connect disparate data systems, relying on patchwork solutions to support AI applications. The urgency has only increased with the rise of AI agents -- software tools capable of performing complex reasoning autonomously. These agents require instantaneous access to live and historical data to function effectively, a demand Microsoft aims to meet with Fabric. And with AI agents becoming one one of the hottest trends for enterprise companies next year, Microsoft is pushing to lead here. See our separate coverage about how Microsoft is ahead in this race, and no one else is close. The integration of Azure SQL is just the beginning of this integration of transactional data. Microsoft plans to extend support to other key transactional databases, including Cosmos DB, its NoSQL document database widely used in AI applications, and PostgreSQL, the popular open-source relational database. While timelines for these integrations remain unspecified, this marks a significant milestone in Microsoft's effort to create a truly unified data platform. Microsoft also said it plans to integrate with popular open source transactional databases, including MongoDB, and Cassandra, but it's unlikely Microsoft will prioritize integration with competing proprietary transactional databases like Couchbase and Google's Bigtable. Arun Ulag, corporate vice president of Azure Data, emphasized in an interview that integrating transactional databases like Cosmos DB into Fabric is critical for enabling next-generation AI applications. For example, OpenAI's ChatGPT -- the fastest-growing consumer AI product in history -- relies on Cosmos DB to power its conversations, context, and memory, managing billions of transactions daily. As AI agents evolve to handle complex tasks like e-commerce transactions, the demand for real-time access to transactional databases will only grow. These agents rely on advanced techniques like vector search, which retrieves data based on semantic meaning rather than exact matches, to answer user queries effectively -- such as recommending a specific book. "You don't have the time to...go run your RAG model somewhere else," Ulag said, referencing retrieval-augmented generation models that combine real-time and historical data. "It has to be just built into the database itself." By unifying operational and analytical capabilities, Fabric allows businesses to build AI applications that seamlessly leverage live transactional data, structured analytics, and unstructured insights. One of the most dynamic announcements in Fabric is the introduction of AI Skills, a capability that enables enterprises to interact with any data - wherever it resides - through natural language. They connect to Copilot Studio, so you can build AI agents that easily query this data across multiple systems, from transactional logs to semantic models. Ulag said that if he had to pick one announcement that excites him the most, it would be AI Skills. With AI Skills, business users can simply point to any dataset -- be it from any cloud, structured, or unstructured - and begin asking questions about that data, whether through natural language, SQL queries, Power BI business definitions, or real-time intelligence engines, he said. For example, a user could use AI Skills to identify trends in sales data stored across multiple systems or to generate instant insights from IoT telemetry logs. By bridging the gap between business users and technical systems, AI Skills simplifies the development of AI agents and democratizes data access across organizations. As of today, AI Skills can connect with lakehouse and data warehouse tables, mirrored DB and shortcut data, and now semantic models and Eventhouse KQL databases. Support for unstructured data is "coming soon," the company said. Microsoft faces fierce competition from players like Databricks and Snowflake on the data platform front, as well as AWS and Google Cloud in the broader cloud ecosystem -- all of which are working on integrating transactional and analytical databases. However, Microsoft's approach with Fabric is beginning to carve out a unique position. By leveraging a unified SaaS model, seamless Azure ecosystem integration, and a commitment to open data formats, Microsoft eliminates many of the data complexities that have plagued enterprise data systems. Additionally, tools like Copilot Studio for building AI agents and Fabric's deep integration across multi-cloud environments give it an edge (see my separate analysis [LINK] of Microsoft's positioning around AI agents, which also appears to be industry-leading). Microsoft's ability to embed AI capabilities directly into its unified data environment "could provide a better experience for developers and data scientists," said Robert Kramer, vice president at research firm Moor Insights, underscoring how Fabric's design simplifies workflows and accelerates AI-driven innovation. Microsoft's strategy to unify and simplify the enterprise data stack not only meets the demands of today's AI-centric workloads but also sets a high bar for competitors in the rapidly evolving data platform market. The integration of transactional databases into Fabric marks a significant milestone, but it also reflects a broader shift across the enterprise data landscape: the race toward seamless interoperability. With AI agents becoming a cornerstone of enterprise strategy, the ability to unify disparate systems into a cohesive architecture is no longer optional -- it's essential. However, Arun Ulag, corporate vice president of Azure Data, acknowledged the challenges that come with operating at Microsoft's scale. While the company has taken major strides with Fabric, the fast-moving nature of the industry demands constant innovation and adaptability. "A lot of these patterns are new," Ulag explained, describing the challenges of designing for a diverse set of use cases across industries. "Some of these patterns will work. Some of them will not, and we'll only know as customers try them at scale...The way it's used in automotive may be very, very different from the way it's used in healthcare," he added, emphasizing the role of external forces like government regulations in shaping future development. As Microsoft continues to refine Fabric, the company is positioning itself as a leader in the shift to unified, AI-ready data architectures. But with competitors also racing to meet the demands of enterprise AI, the journey ahead will require constant evolution, rapid learning, and a focus on delivering value at scale. For more insights into the announcements and Arun Ulag's perspective, watch our full video interview above.

Microsoft puts transactions, analytics on single DB service

Windows giant also improving Iceberg support after throwing lot in with Delta Parquet Ignite Microsoft is set to launch a database service that can manage transactional and analytical workloads in the same system. The software and cloud giant also promises greater support for the Iceberg table format preferred by rivals, increasing the interoperability with the native Delta in its Fabric data platform. Last year, Microsoft launched Fabric, a new data platform that strove to bring together different data systems and services already existing in its Azure cloud, along with some new features. Notable among them was mirroring, which the vendor said replicates a snapshot of the external database to OneLake in Delta Parquet tables and keeps the replica synced in "near real time." At Microsoft's Ignite conference this week, the vendor launched an approach to bringing together transactional and analytical workloads in a single system within Fabric. In a blog post, Microsoft previewed Fabric Databases, which it said represented "a new class of cloud databases that bring together transactional and analytical workloads, creating a truly unified data platform." It said: "Developers can streamline application development with simple, autonomous, and optimized for AI databases that provision in seconds and are secured by default with features like cloud authentication and database encryption." Microsoft said features such as vector search, RAG support, and Azure AI integration would simplify AI application development. Meanwhile, user data would be "instantly available" in OneLake, Microsoft's lakehouse product, which brings together data warehouse and data lake-type workloads. The combined analytics/transactional service is set to be first available in Fabric as a service based on the SQL Server engine, related to Microsoft's popular database product. Arun Ulagaratchagan, corporate vice president Azure Data, told The Register that the database service would "combine operational data with analytics and AI into a converged data platform that unlocks new scenarios for insight-driven applications." Fabric Databases would include Azure Cosmos DB and Azure Database for PostgreSQL - already available in Azure - down the line, the vendor said. Ulagaratchagan said including these services in the Fabric Database would make it "easier for developers to deliver consistent performance even when running spiky workloads, due to features like serverless, auto-scaled compute and storage, and intelligent auto-indexing." He said the database service would perform both analytical and transactional workloads - usually in separate column and row-oriented systems, respectively - by automatically replicating data to Microsoft OneLake and making it available to the analytical engines within Microsoft Fabric. While relatively novel, the effort to bring together transactional and analytics workloads is not unique. Fabric rival Snowflake has launched its Unistore product after previewing the system more than two years ago. Siemens AG is among the customers. Its Hybrid Tables "intelligently identify when a query is transactional or analytical," the vendor said. It stores the data in both row and column formats. Database SingleStore, which launched in 2019, uses a single representation of the data where the row store is log-structured to tackle the same problem. Microsoft's Ulagaratchagan said: "We have a complete relational store that supports transaction logs along with columnstore indexes, so you can store data in row and column format. Additionally, data is replicated in near real-time to OneLake as delta parquet." Microsoft has also announced developments in its handling of open table formats, which allows users to bring their own query engines to data, without having to move it into another system. Microsoft's native format is Delta, developed by Databricks and now an open source project managed by the Linux Foundation. In January last year, Microsoft said it would also support rival formats Iceberg and Hudi - both Apache projects - externally. Last week, Microsoft said customers could now consume Iceberg-formatted data across Microsoft Fabric without data movement or duplication using OneLake shortcuts. It also said Snowflake added the ability to write Iceberg tables directly to OneLake, making it even easier for customers to use both Snowflake and Fabric. "We have nothing new to share at this time regarding Hudi," Ulagaratchagan said. However, he said Delta would remain the native format, despite AWS, Cloudera, Google, and Snowflake all supporting Iceberg as their preferred format. Last month, former Apple software engineering manager Russell Spitzer - now with Snowflake - said he expected Iceberg to become the dominant format as it gathers vendor support. "Fabric was optimized from the ground up for the Delta Parquet format," he said. "When we launched Fabric, we committed to making a completely open platform with full interoperability with our partners so our customers can have the flexibility to do what makes sense for their business. That's the reason we standardized Fabric on the open Delta Parquet format and it's the reason we are ensuring customers can access all data sources in Iceberg format, including the Iceberg sources from Snowflake. "With our latest announcements, customers will get similar performance from either Iceberg or Delta Parquet formats so we've removed any reason to switch." ®