One logical copy (Preview)

You can create a one logical copy of KQL Database data by turning on OneLake availability. Turning on OneLake availability means that you can query the data in your KQL database in Delta Lake format via other Fabric engines such as Direct Lake mode in Power BI, Warehouse, Lakehouse, Notebooks, and more.

Important

This feature is in preview.

Delta Lake is a unified data lake table format that achieves seamless data access across all compute engines in Microsoft Fabric. For more information on Delta Lake, see What is Delta Lake?.

In this article, you learn how to turn on availability of KQL Database data in OneLake.

How it works

The following table describes the behavior of your KQL database and tables when you turn on or turn off OneLake availability.

Turned on Turned off
KQL Database - Existing tables aren't affected. New tables are made available in OneLake.
- The Data retention policy of your KQL database is also applied to the data in OneLake. Data that's removed from your KQL database at the end of the retention period is also removed from OneLake.
- Existing tables aren't affected. New tables won't be available in OneLake.
A table in KQL Database - New data is made available in OneLake.
- Existing data isn't backfilled.
- Data can't be deleted, truncated, or purged.
- Table schema can't be altered and the table can't be renamed.
- New data isn't made available in OneLake.
- Data can be deleted, truncated, or purged.
- Table schema can be altered and the table can be renamed.
- Data is soft deleted from OneLake.

Important

There's no additional storage cost to turn on OneLake availability. For more information, see resource consumption.

Prerequisites

Turn on OneLake availability

You can turn on OneLake availability either on a KQL database or table level.

  1. To turn on OneLake availability, browse to the details page of your KQL database or table.

  2. Next to OneLake availability in the Database details pane, select the Edit (pencil) icon.

    Screenshot of the Database details pane in Real-Time Analytics showing an overview of the database with the edit OneLake availability option highlighted.

  3. Turn on the feature by toggling the button to Active, then select Done. The database refreshes automatically.

    Screenshot of the OneLake folder details window in Real-Time Analytics in Microsoft Fabric. The option to expose data to OneLake is turned on.

You've turned on OneLake availability in your KQL database. You can now access all the new data added to your database at the given OneLake path in Delta Lake format. You can also choose to create a OneLake shortcut from a Lakehouse, Data Warehouse, or query the data directly via Power BI Direct Lake mode.

View files

When you turn on OneLake availability on a table, a delta log folder is created along with any corresponding JSON and parquet files. You can view the files that were made available in OneLake and their properties while remaining within Real-Time Analytics.

Important

It might take up to a few hours for the files to appear after turning on OneLake availability.

  • To view the files, hover over a table in the Explorer pane and then select the More menu [...] > View files.

    Screenshot of the Explorer pane showing the More menu dropdown of a table.

  • To view the properties of the delta log folder or the individual files, hover over the folder or file and then select the More menu [...] > Properties.

  • To view the files in the delta log folder:

    1. Select the _delta_log folder.
    2. Select a file to view the table metadata and schema. The editor that opens is in read-only format.

Data types mapping

Event house to Delta parquet data types mapping

Event house data types are mapped to Delta Parquet data types using the following rules. For more information on Event house data types, see Scalar data types.

Event house Data Type Delta Data Type
bool boolean
datetime timestamp OR date (for date-bound partition definitions)
dynamic string
guid string
int integer
long long
real double
string string
timespan long
decimal decimal(38,18)