Data in OneLake can be addressed as if it were one big ADLS storage account for the entire organization. OneLake supports the same ADLS Gen2 APIs and SDKs to be compatible with existing ADLS Gen2 applications including Azure Databricks. All tabular data is stored in OneLake in delta parquet format. This means when a data engineer loads data into a lakehouse using Spark and a SQL developer in a fully transactional data warehouse uses T-SQL to load data, everyone is still contributing to building the same data lake. All Fabric data items like data warehouses and lakehouses store their data automatically in OneLake in delta parquet format. Built on top of Azure Data Lake Storage Gen2, OneLake can support any type of file, structured or unstructured.
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Items can give tailored experiences for each persona such the Spark developer experience in a lakehouse.įor more information on how to get started using OneLake, see Creating a lakehouse with OneLake. Similar to how Office stores Word, Excel, and PowerPoint files in OneDrive, Fabric stores lakehouses, warehouses, and other items in OneLake. Within a workspace, you can create data items and all data in OneLake is accessed through data items. Each workspace is part of a capacity that is tied to a specific region and is billed separately. Workspaces enable different parts of the organization to distribute ownership and access policies. Within a tenant, you can create any number of workspaces. While all data is within the boundaries set by the tenant admin, it's important that this admin doesn't become a central gatekeeper preventing other parts of the organization from contributing to OneLake. Any data that lands in OneLake is governed by default. Knowing where a customer’s organization begins and ends, provides a natural governance and compliance boundary, which is ultimately under the control of a tenant admin. The concept of a tenant is a unique benefit of a SaaS service. Governed by default with distributed ownership for collaboration OneLake is provisioned automatically with every Fabric tenant with no extra resources to set up or manage. There can never be more than one and if you have Fabric, there can never be zero. Every customer tenant has exactly one OneLake. OneLake focuses on removing these challenges by improving collaboration. Prior to OneLake, it was easier for customers to create multiple lakes for different business groups rather than collaborating on a single lake, even with the extra overhead of managing multiple resources.
One data lake for the entire organization
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