What is OneLake in Microsoft Fabric?

OneLake is the unified storage layer for Microsoft Fabric — think of it as "OneDrive for data." It automatically provisions storage for every Fabric workspace and stores all data in open Delta Parquet format. Every Fabric workload (lakehouses, warehouses, Power BI, notebooks) reads from and writes to OneLake, eliminating data silos and duplication. Unlike traditional data lakes that require manual provisioning and management, OneLake is fully managed with built-in governance.

Does OneLake cost extra beyond Fabric capacity?

OneLake storage is included with your Fabric capacity subscription at no additional storage cost for data stored within Fabric. The capacity pricing covers both compute (CUs) and storage. However, if you use shortcuts to reference data in external Azure Data Lake Storage, S3, or GCS, you still pay for storage in those external services. OneLake actually reduces total storage costs by eliminating the need to copy data between services.

Can OneLake connect to data in AWS S3 or Google Cloud?

Yes, OneLake shortcuts can reference data in Amazon S3 and Google Cloud Storage. The data appears in OneLake as if it were local, but no data is copied — queries are routed to the external storage. This enables cross-cloud analytics where you can combine AWS/GCP data with Azure/OneLake data in the same queries and Power BI reports. Authentication is managed through workspace settings with appropriate credentials for the external storage.

OneLake: The Definitive Guide to Microsoft Fabric's Unified Data Lake

OneLake is the storage foundation of Microsoft Fabric — a single, unified data lake for your entire organization. Think of it as the "OneDrive for data." With 3,600 monthly searches, OneLake represents a fundamental shift in how organizations store and access analytical data.

What Is OneLake?

OneLake is automatically provisioned for every Microsoft Fabric tenant. It provides: - Single storage layer — All Fabric workloads (Lakehouse, Warehouse, Power BI, notebooks) read from and write to OneLake - Open formats — Data stored as Delta Parquet (tables) and standard files (CSV, JSON, Parquet) - No data duplication — A table created by a Spark notebook is immediately queryable by SQL, Power BI, and other workloads - Organizational scope — One OneLake per tenant, organized by workspaces

Architecture

OneLake follows a hierarchical structure: - Tenant → One OneLake per Fabric tenant - Workspace → Organizational container (like a folder) - Item → Lakehouse, Warehouse, Semantic Model - Tables → Delta tables in open format - Files → Raw files (CSV, JSON, Parquet, images)

Every workspace automatically gets OneLake storage. No provisioning, no storage accounts, no access keys to manage.

Shortcuts: Virtual Data References

OneLake shortcuts are virtual references to data stored elsewhere. They appear as if the data is in OneLake, but no data is copied:

Supported Shortcut Targets - Other OneLake locations — Reference tables from other workspaces - Azure Data Lake Storage Gen2 — Connect to existing ADLS accounts - Amazon S3 — Cross-cloud access to AWS storage - Google Cloud Storage — Cross-cloud access to GCP storage - Dataverse — Direct access to Dynamics 365 data

Benefits of Shortcuts - Zero data movement — No ETL needed - Real-time access — Changes in the source appear immediately - Cost savings — Avoid data duplication storage costs - Governance — Source controls access, OneLake provides discovery

Learn more in our OneLake shortcuts guide.

Delta Format: The Storage Standard

All table data in OneLake is stored in Delta Lake format: - ACID transactions — Reliable read/write with isolation - Time travel — Query historical versions of data - Schema evolution — Add columns without rebuilding - Optimized storage — Automatic compaction, Z-ordering, and V-ordering - Open format — Any Spark, SQL, or Python tool can read Delta tables

Security Model

OneLake security operates at multiple levels:

Workspace Security - Admin, Member, Contributor, Viewer roles - Controls who can create, edit, and view items

Item-Level Security - Share individual lakehouses, warehouses, or reports - Fine-grained access without workspace membership

Row-Level Security (RLS) - Define DAX filters that restrict data visibility - Applied in semantic models and enforced across all consumers

OneLake Data Access Roles (Preview) - Folder-level security within a lakehouse - Control access to specific tables or file directories

See our Fabric security guide for implementation details.

Direct Lake: The Performance Revolution

Direct Lake mode is enabled by OneLake's architecture. Instead of importing data into Power BI's in-memory engine (Import mode) or querying the source in real-time (DirectQuery), Direct Lake reads Delta Parquet files directly from OneLake:

Mode	Speed	Freshness	Model Size Limit
Import	Fastest	Stale until refresh	1-100 GB
DirectQuery	Slowest	Real-time	Unlimited
Direct Lake	Fast (near-Import)	Near real-time	100+ GB

Learn more in our Direct Lake guide.

OneLake vs. Traditional Data Lakes

Feature	Traditional Data Lake (ADLS)	OneLake
Provisioning	Manual	Automatic
Access management	Azure IAM + ACLs	Workspace roles
Storage format	Any (often unmanaged)	Delta Parquet (managed)
Query by Power BI	Requires Import/DQ	Direct Lake
Cross-workload access	Manual integration	Automatic
Governance	External tools	Built-in catalog
Shortcuts	Not available	Virtual references

Getting Started

Access Fabric — Sign in to app.fabric.microsoft.com
Create a Workspace — OneLake storage is automatically provisioned
Create a Lakehouse — Provides Tables and Files sections
Load data — Upload files, create notebooks, or build pipelines
Query data — Use SQL, Spark, or Power BI Direct Lake

For enterprise OneLake implementation, our Microsoft Fabric consulting team provides architecture design, migration planning, and governance setup. Contact us.