Microsoft's BI suite, integrated natively into Fabric, with Direct Lake mode over OneLake tables.
Microsoft Fabric Profiled
A SaaS analytics platform that unifies data engineering, warehousing, real-time analytics, data science and Power BI on a single lake (OneLake).
At a glance
Microsoft Fabric is Microsoft's all-in-one SaaS analytics platform. Instead of assembling separate Azure services, teams get data integration, lakehouse, warehouse, real-time analytics, data science and Power BI in one product. All of it shares one storage layer, OneLake, and one capacity-based bill.
Where it fits
- Strongest when: the organisation already uses Microsoft 365, Power BI and Azure, and wants one managed platform with little infrastructure to run.
- Consider carefully when: you need to run on AWS or GCP, or want fine control over compute clusters.
Key concepts
- Tenant → Capacity → Workspace → Item: how Fabric resources are organised.
- OneLake: one logical lake per tenant; every item's data is stored there in Delta/Parquet format.
- Shortcuts & Mirroring: reach data in other stores without building ETL.
- Direct Lake: Power BI reads Delta tables in OneLake directly, without import or DirectQuery.
In the tool landscape (4)
- Data Factory in Microsoft Fabric — Pipelines and Dataflow Gen2 for ingesting and transforming data in Microsoft Fabric.
- Microsoft Fabric — SaaS analytics platform that unifies data engineering, warehousing, real-time analytics and Power BI on OneLake.
- Microsoft Fabric Data Warehouse — T-SQL data warehouse in Microsoft Fabric that stores its tables in Delta format in OneLake.
- Power BI — Microsoft's BI platform for semantic models, reports and dashboards, integrated with Fabric.
Products (11)
BI & Analytics
Data Engineering (Spark & Notebooks)
Managed Spark with notebooks, Spark job definitions and environments.
Data Integration (ETL/ELT)
Pipelines and Dataflow Gen2 for ingesting, transforming and orchestrating data.
Continuously replicates external databases into OneLake as Delta tables, with near real-time freshness.
Data Lake & Storage
A single, tenant-wide logical data lake that stores all Fabric data in Delta/Parquet format, with shortcuts to external storage.
Data Science & ML
Notebook-based ML with MLflow experiment tracking and model management.
Data Warehouse
A fully managed T-SQL warehouse that stores its tables as Delta in OneLake.
Generative AI & Agents
AI assistance across Fabric workloads, plus data agents for natural-language Q&A over data.
Lakehouse
A Fabric item that combines files and Delta tables in OneLake, with an automatically generated SQL analytics endpoint.
Operational Database
Preview
An operational SQL database in Fabric that automatically replicates to OneLake for analytics.
Streaming & Real-Time
Streaming ingestion, KQL-based Eventhouses, real-time dashboards and event-driven actions.
Upcoming events
User group · In person
RLS Without Compromise & Advanced Time Intelligence in Power BI
Tue, 24 Nov 2026, 18:00–21:00 CET
Zaventem, Belgium
- Free
User group · Online
Agentic Coding in a Real-Life Data Platform Migration
Tue, 8 Dec 2026, 18:30–19:45 CET
Online (Microsoft Teams)
- Free
Conference · In person
FabCon + SQLCon 2027
Mon, 8 Mar 2027 – Fri, 12 Mar 2027
Atlanta, United States
- Price not stated
From the blog
Data architecture patterns: what actually competes with what
6 October 2026
Lambda, Kappa, Lakehouse, Mesh, Medallion. They get set out side by side as though the job is to pick one. They answer different questions, and a real platform runs several at once.
Fabric Conference 2025, Vienna, Austria – Key Takeaway
8 November 2025
The central message from Fabric Conference 2025 is clear: Microsoft Fabric is now ready for production deployment.
Data sovereignty in cloud data platforms: what to check before you choose
5 August 2025
Residency is not sovereignty. A practical guide to the legal, operational and architectural questions to ask of Microsoft Fabric, Databricks, Snowflake, and any other cloud data platform.
Capability snapshot
4 partial · 21 native · 5 unknown
| Capability | Support | Notes |
|---|---|---|
| Platform & Deployment | ||
| Cloud availability | Partial | Runs on Azure only; OneLake shortcuts can reference data in AWS S3, Google Cloud Storage and others. |
| Deployment model | Native | Fully SaaS; no clusters or infrastructure in the customer's subscription. |
| Pricing model | Native | Capacity-based (CU). |
| Storage & Formats | ||
| Open table formats | Native | Delta Lake (Parquet) is the native table format in OneLake; Iceberg interoperability is available. Verify its current status. |
| Storage/compute separation | Native | OneLake storage is decoupled from capacity compute. |
| Query external data in place | Native | Shortcuts and mirroring bring external data into OneLake without traditional ETL. |
| Compute & Workloads | ||
| SQL warehousing | Native | |
| Serverless compute | Native | All compute is managed by the SaaS capacity model. |
| Spark & notebooks | Native | |
| Languages | Native | SQL (T-SQL), Python/PySpark, Scala, R, KQL, DAX. |
| Integration & Pipelines | ||
| Managed ingestion connectors | Native | |
| Declarative transformation pipelines | Unknown | Dataflow Gen2 (Power Query) and materialized lake views. Assess how they compare with declarative pipelines elsewhere. |
| Orchestration | Native | |
| Streaming / real-time | Native | |
| Governance & Security | ||
| Unified catalog | Native | OneLake catalog, with Microsoft Purview integration. |
| Lineage | Native | Workspace lineage view; Purview for broader lineage. |
| Row/column-level security | Unknown | RLS/CLS exist in the warehouse and semantic models; OneLake security scope is evolving. Verify. |
| Sharing & Collaboration | ||
| Cross-organisation data sharing | Partial | External data sharing between Fabric tenants. Verify current scope. |
| Data marketplace | Unknown | |
| Data clean rooms | Unknown | |
| Analytics, ML & AI | ||
| Native BI / dashboards | Native | |
| ML lifecycle | Partial | MLflow-based experiments and models in Fabric Data Science; production model serving is typically done through Azure services. |
| LLM functions in SQL | Unknown | AI functions exist for notebooks and dataframes. Verify SQL availability. |
| Natural-language querying / data agents | Native | Copilot in Fabric and Fabric data agents. |
| Operational (OLTP) database | Partial | SQL database in Fabric; check GA/preview status and other database options. |
| Unification | ||
| Lifecycle coverage | Native | Answers integration, data, metadata, visualisation, AI/ML and much of governance with its own components - Data Factory, Lakehouse, Warehouse, Real-Time Intelligence, Power BI and Data Science. |
| Shared storage | Native | OneLake is included automatically in every tenant and is the single store for all analytics data. Microsoft's own wording is "one copy of data to use with multiple analytical engines without duplication", in Delta Parquet or Iceberg. |
| Shared governance | Native | Governance and security are built into OneLake itself rather than applied per engine, so policy follows the data across experiences. |
| Shared metadata and identity | Native | One tenant-wide lake with a single catalogue across every workload; items are tenant objects rather than per-service resources. |
| Sold as one platform | Native | Bought as Fabric capacity, with the experiences drawing on the same capacity rather than being licensed separately. |