Data management
Real-Time Intelligence offers a range of options for managing your data, both on a database and table level. You can manage your data either through the UI of your KQL database or by using management commands. Management commands, also known as control commands, are requests to the service to retrieve information that isn't necessarily data in the database tables, or requests to modify the service state.
For more information, see Management commands
Note
Managed identities are not supported in Microsoft Fabric.
Data retention policy
The retention policy controls the mechanism that automatically removes data from tables or materialized views.
For more information, see Data retention policy.
Caching policy
The caching policy allows to you to choose which data should be cached and kept in local SSD storage.
For more information, see Caching policy.
One logical copy
To expose the data in your KQL database to all Microsoft Fabric experiences, create a OneLake shortcut.
For more information, see One logical copy.
Table update policy
When you trigger an update policy with a command that adds data to a source table, data also appends to a target table. The target table can have a different schema, retention policy, and other policies from the source table.
For more information, see Create a table update policy.
Materialized views
A materialized view is an aggregation query over a source table, or over another materialized view. It represents a single summarize
statement. You can create materialized views using the .create materialized-view
command.
For more information, see Create materialized views
Stored functions
This feature allows you to create or alter an existing function using the .create-or-alter
function
command, which stores it in the database metadata. If the function with the provided functionName doesn't exist in the database metadata, the command creates a new function. Otherwise, the named function is changed.
For more information, see Create stored functions