Microsoft Fabric Expands with LinkedIn's Graph Database and Geospatial Capabilities

Enterprise AI success is about more than just data it's about knowledge - Here's how Microsoft Fabric is set to solve that challenge with LinkedIn's graph database technology

Without data, enterprise AI isn't going to be successful. Getting all the data in one place and having the right type of data tools, including connections to different types of databases is a critical aspect of having the right data for AI. There are multiple vendors all vying to be the data platform of choice for enterprises today, with Databricks, Snowflake, Google and Amazon among the big options. Microsoft has increasingly been active in the space with its Microsoft Fabric technology first announced in 2023 and expanded in the years since with data tools to accelerate AI workflows. In 2024, Microsoft claimed that 70% of the Fortune 500 used Fabric, now in 2025 that figure has moved higher to 80%. Microsoft Fabric is a unified data platform that combines data lakes, databases, data warehouses, real-time analytics and business intelligence into a single service. It eliminates the complexity of managing multiple data tools while providing the Microsoft OneLake, which is a virtualization layer that can connect to data across clouds without requiring migration. Microsoft is now integrating LinkedIn's proven graph database technology into the platform. The graph database addition addresses a fundamental challenge plaguing enterprise AI deployments. Vector databases excel at semantic search, but they struggle to understand relationships between data entities. Graph databases fill this gap by modeling connections between customers, suppliers, network devices, or any business entities. This creates a knowledge graph that provides crucial context for AI applications. "Graph databases are incredibly important because you know there is only so much data you can put into perfectly structured tables," Arun Ulag, corporate vice president for Azure Data at Microsoft, told VentureBeat. "The actual world that we live in is full of relationships, relationships between people, relationships between customers, relationships within suppliers, the way supply chains work the way cloud systems work, everything is connected and you really need a very good graph database." LinkedIn's enterprise graph engine comes to Fabric The graph capability isn't built from scratch. Microsoft moved a substantial portion of LinkedIn's graph database team into Azure Data approximately 18 months ago. The goal was to adapt the technology that powers LinkedIn's massive social network for enterprise use cases. "The graph database allows you to collect the set of entities that matter for you to be able to run your vector search on," Ulag explained. "Graph databases narrow the solution space into the ones that matter, and then the vector index allows you to go zoom in even further." The technical implementation reveals Microsoft's strategy for optimizing AI performance through a two-stage data narrowing process. First, the graph database identifies relevant entities based on relationships. For example, all suppliers connected to a specific customer or all network devices linked to a particular data center. Then, vector search operates within that constrained set to find semantically relevant information. This approach could significantly improve AI response accuracy and speed. Rather than searching across an entire data lake for relevant information, AI systems can focus on a pre-filtered set of connected entities. This reduces both computational overhead and the risk of retrieving irrelevant data. The graph database supports standard GraphQL queries and integrates with Fabric's existing data lake architecture with all data remaining available in open-source data formats. Beyond social networks: Enterprise graph use cases Graph databases have traditionally been associated with social networks and fraud detection. However, Microsoft and industry analysts see broader applications emerging, particularly for agentic AI systems that require persistent memory and context. "Graph databases can help with some very old, but some very well established use cases like fraud detection, which they're great at that, but they can also serve as some very modern, forward looking capabilities, such as bringing a memory to an agentic system," Brad Shimmin, VP and Practice Lead for Data and Analytics at Futurum Group, told VentureBeat. The graph database also strengthens Microsoft's competitive position against Databricks, Snowflake and Google Cloud's data platforms. According to Futurum Group's analysis, Microsoft Fabric ranks in the "Elite category" alongside Google and Databricks. But the graph capability provides a differentiator that competitors currently lack. "Microsoft bringing Graph into fabric, it's a no brainer," Shimmin noted. Microsoft's approach integrates graph capabilities directly into the data platform rather than offering it as a separate service. This aligns with the broader industry trend toward unified data intelligence platforms. The integration means enterprises can work with graph, vector, geospatial and traditional relational data within a single platform. They avoid complex data movement or synchronization. More data sources come to Fabric Beyond graph databases, Microsoft announced several other Fabric enhancements that strengthen its enterprise positioning: * Expanded data source integration: New mirroring capabilities for Oracle databases and Google BigQuery allow enterprises to virtualize data from these sources in near real-time. * Enhanced geospatial capabilities: Native mapping functionality, powered by Azure Maps technology, enables large-scale geospatial analysis integrated with real-time data streams. This could prove valuable for logistics, retail and IoT applications. * Developer experience improvements: The new Fabric Extensibility Toolkit and Model Context Protocol (MCP) integration make it easier for developers to build custom applications and integrate with AI development tools. Enterprise evaluation framework Industry analysts offer specific guidance for enterprises evaluating data platforms. From a technical perspective, Shimmin identifies five critical capabilities enterprises should evaluate: Gartner which also ranks Microsoft Fabric highly also suggests that enterprise alignment is a critical part of the decision making process. "Enterprises evaluate data management vendors by aligning their data and analytics strategy to technology choices, including database management, data integration, metadata management, and related categories," Gartner analyst Thornton Craig, told VentureBeat. "Data management platforms, including Microsoft Fabric, offer a comprehensive vision for overall data management." Strategic implications for AI adopters Having a flexible data platform that handles all data type should be table stakes for any enterprise serious about its AI strategy. The open approach that Microsoft has taken with Fabric, enabling it to connect, mirror and use all types of data is an attractive feature to many enterprises. The graph database integration signals Microsoft's broader strategy of building AI-ready data infrastructure rather than simply adding AI features to existing platforms. For enterprises already committed to Microsoft's ecosystem, the graph capability provides immediate value without additional vendor relationships or data movement. However, organizations should approach platform decisions strategically. "The trick is to be able to kind of align the solutions you're looking at with both the outcome of what you're trying to do, are you trying to save money or trying to make money, and how well that aligns with the estate that you're sitting on," Shimmin advised. "If you're sitting on a data swamp and everything's a mess and you can't get to it, you're going to need to invest in a platform that's very flexible in terms of being able to adapt and bring in a lot of different and disparate data sources."

Microsoft expands Fabric with LinkedIn-based graph engine, real-time maps - SiliconANGLE

Microsoft expands Fabric with LinkedIn-based graph engine, real-time maps Microsoft Corp. today is expanding its Fabric data platform with the addition of native graph database and geospatial mapping capabilities, saying the enhancements enhance Fabric's capacity to power artificial intelligence-driven, data-centric applications in large enterprises. Fabric is a cloud-based data and analytics platform designed to unify most aspects of the data lifecycle, from storage and integration to real-time analytics and business intelligence. It combines a data lake called OneLake with data engineering, data science and AI tooling. Microsoft claims more than 25,000 customers have adopted Fabric since it was introduced in 2023. The addition of a graph database and geospatial features fills key gaps in the Fabric lineup. Graph databases store and analyze relationships between data, making them a popular choice for understanding complex, interconnected information like social networks, supply chains and recommendation engines. Graph capabilities were "perhaps the last big missing piece" in Fabric, said Arun Ulagaratchagan, corporate vice president of Azure Data at Microsoft. The underlying technology comes from LinkedIn, the business social network Microsoft acquired in 2016. The graph database LinkedIn built to map connections between its 1.2 billion registered members is one of the world's largest, Ulagaratchagan said. Microsoft reassigned some members of the LinkedIn team to work on Fabric 18 months ago. Fabric's new graph engine is cloud-native, with a scale-out, distributed architecture. Microsoft said the graph database overlays directly on top of OneLake and provides the full range of graph capabilities. "This is a pure-play native graph database," Ulagaratchagan said. "You do not need to extract data and move it. The graph database works natively on top of OneLake." Graphs are valuable in AI because they can interpret how entities like people and events are connected to enable deeper reasoning and more accurate responses. They also power knowledge graphs, which help AI applications, such as recommendation engines and virtual assistants, deliver personalized results. Ulagaratchagan said Microsoft's embedded graph model is as powerful as commercial offerings from Microsoft partners like Neo4j Inc. and TigerGraph Inc. but carries no additional cost. "The graph database lights up for every Fabric customer," he said, adding that Microsoft intends to maintain its partnership arrangements with those two companies. Fabric's new geospatial mapping capability enables interactive, real-time visualizations from both batch and live streaming data. Such capabilities can be used to track retail foot traffic, optimize logistics routes and coordinate responses to natural disasters. "You can map your batch and real-time data and see it flowing through the graphs," Ulagaratchagan said. "For example, you might show the distribution of your stores across the U.S., with footfall in real time." Fabric's mapping layer builds on Azure's event streaming infrastructure, which integrates batch and real-time data from sources like Azure Event Hubs, Amazon Web Services Inc.'s Kinesis, and Google LLC's PubSub. While graph and geospatial databases are the spotlight additions, Microsoft is also announcing broader updates to Fabric. OneLake mirroring has been expanded to support Oracle Corp. and Google BigQuery data warehouses, enabling near real-time replicas in open source formats. Workspace-level IP filtering is now available along with expanded support for Azure Private Links, which is used for secure connections between Azure virtual networks and on-premises networks. Developer tools are being enhanced with the addition of Model Context Protocol support and a new extensibility toolkit. Git-based pipelines have also been extended to more Fabric assets. Ulagaratchagan said the objective of Fabric has always been about unification: "All of these capabilities that were discrete -- SQL databases, NoSQL databases, analytics databases and lakehouses -- are collapsing into one integrated platform," he said. Microsoft will continue its cadence of weekly updates and maintain its public Fabric roadmap.