Introducing Graph in Microsoft Fabric – Connected Data for the Era of AI
Modern businesses are drowning in complexity. Logistics teams wrestle with multi-hop dependencies and fragmented asset tracking. Banks face slow fraud detection and cumbersome processes that require stitching data across silos. E-commerce platforms struggle to deliver personalized experiences because customer journeys and product catalogs are deeply interconnected.
The common thread? Traditional relational models and complex joins can’t keep up with the complexity and depth of these relationships. That’s where graph analytics comes in. By modeling data as networks of entities and relationships, graph analytics unlocks insights hidden in connections -enabling faster fraud detection, smarter recommendations, optimized supply chains, and a true 360° view of customers.
Microsoft Fabric has launched an integrated graph data management, analytics, and visualization service. Its horizontally scalable, native graph engine empowers enterprises of all sizes with a relationship first way to model and explore interwoven data across the organization. Leveraging the power of OneLake as the single, unified, logical data lake for your whole organization, businesses can quickly and easily build a graph connecting data from sales, marketing, customer service, operations and more to truly find insights hidden in those vast relationships.
Delivered through Fabric’s usable and consistent governed experience, this graph service helps organizations see how everything connects, act with confidence, and avoid heavy ETL pipelines that duplicate data in separate graph databases.
Graph in Microsoft Fabric will roll out to various regions starting on 1 October 2025. Check the community and release plans for the latest information: https://aka.ms/graphavailability
Why graph, and why now?
Modern organizations don’t just have more data; they have more relationships across all that data.
Take Banking for example:
- Accounts → Transactions → Merchants → Risk Scores
Traditional, join-heavy approaches struggle when questions jump multiple ‘hops’ like above, or when patterns hide in the relationships themselves, such as the following examples:
- Transactions linked to high-risk merchants.
- Accounts associated through shared devices or IP addresses.
These relationship-centric questions are critical for fraud detection, compliance, and real-time risk assessment, yet they’re painfully slow with conventional methods. Graph analytics makes these queries intuitive and fast by modeling data as connected networks rather than rigid tables.
Examples like this exists across all different industries and verticals. Graph places connections at the center so you can trace multi‑hop paths, reason about relationships, and surface insights that are hard to see in rows and columns. Graph in Microsoft Fabric enables you to explore deep relationships (multi‑hop, self‑referential) without complex query gymnastics, as well as to filter and group by degrees of connection to reveal unobvious clusters and paths.
When paired with generative AI, graph provides grounding that makes answers more accurate and explainable. LLMs and agents’ abilities to reason are reinforced by contexts:
- What’s related to what
- How they are associated
- What else is relevant and why
Meaning higher-quality answers, safer automations, and more reliable orchestration across multiple tools or agents.
Made for every role
Graph in Microsoft Fabric is designed to enable everyone to participate in connected insights:
- Business users visually explore relationships and ask natural‑language questions that resolve into graph queries.
- Analysts build patterns and filters with a no/low‑code query experience, switching between diagram and table views to validate results.
- Data engineers define models and map nodes/edges to OneLake data sources with low/no‑code tooling, then publish reliable graph artifacts.
- Developers connect AI agents and apps to the graph, infusing real‑time decisions with context from relationships.
This support for a wide range of user roles and skill levels is possible with the power of the Graph capabilities in Fabric, along with intuitive and user-friendly experiences. With simple low- and no-code tools and natural language querying, users of all skill levels can build graph models in minutes, exploring connections and multi-hop dependencies across customers, assets, suppliers, and systems. And for advanced users, we also provide a rich query editor supporting GQL, giving full flexibility to craft complex graph queries with precision.
Get started today charting new paths with graph
Start thinking in relationships. Identify where multi-hop questions or hidden patterns are slowing you down today and simplify those complexities with graph. Your first use case might be fraud rings, supply chains, customer journeys, asset hierarchies, or countless others, anywhere connections matter. Graph technology is no longer a “nice to have”; it’s a strategic necessity for any organization looking to compete and innovate in a connected economy. Graph in Microsoft Fabric helps you unlock more value from interconnected data and makes it more accessible to everyone, not just specialists.
Explore additional resources on Graph and Real-Time Intelligence
Learn more
- Graph documentation
- Find customer success stories: Fabric Customer Success
Engage
- Submit ideas and vote: Fabric Ideas
- Ask questions on the: Real-Time Intelligence Forum
- Sign up for private preview of natural language querying of Graph
Stay updated
- Microsoft Fabric Blog
- Microsoft Fabric YouTube Channel
- Follow on LinkedIn: Follow Real-Time on LinkedIn
- Check the Microsoft Fabric Release Plan
