Disclaimer: This is work in progress intended to consolidate information from various sources for learning purposes. For the latest information please consult the documentation (see the links below)!
Last updated: 23-May-2025
[Microsoft Fabric] Warehouse Snapshots
- {def} read-only representation of a warehouse at a specific point in time [1]
- allows support for analytics, reporting, and historical analysis scenarios without worrying about the volatility of live data updates [1]
- provide a consistent and stable view of data [1]
- ensuring that analytical workloads remain unaffected by ongoing changes or ETL operations [1]
- {benefit} guarantees data consistency
- the dataset remains unaffected by ongoing ETL processes [1]
- {benefit} immediate roll-Forward updates
- can be seamlessly rolled forward on demand to reflect the latest state of the warehouse
- ⇒ {benefit} consumers access the same snapshot using a consistent connection string, even from third-party tools [1]
- ⇐ updates are applied immediately, as if in a single, atomic transaction [1]
- {benefit} facilitates historical analysis
- snapshots can be created on an hourly, daily, or weekly basis to suit their business requirements [1]
- {benefit} enhanced reporting
- provides a point-in-time reliable dataset for precise reporting [1]
- ⇐ free from disruptions caused by data modifications [1]
- {benefit} doesn't require separate storage [1]
- relies on source Warehouse [1]
- {limit} doesn't support database objects
- {limit} capture a state within the last 30 days
- {operation} create snapshot
- via New warehouse snapshot
- multiple snapshots can be created for the same parent warehouse [1]
- appear as child items of the parent warehouse in the workspace view [1]
- the queries run against provide the current version of the data being accessed [1]
- {operation} read properties
- via
- GET https://api.fabric.microsoft.com/v1/workspaces/{workspaceId}/items/{warehousesnapshotId} Authorization: Bearer <bearer token>
- {operation} update snapshot timestamp
- allows users to roll forward data instantly, ensuring consistency [1]
- use current state
- via ALTER DATABASE [<snapshot name>] SET TIMESTAMP = CURRENT_TIMESTAMP;
- use point in time
- ALTER DATABASE snapshot SET TIMESTAMP = 'YYYY-MM-DDTHH:MM:SS.SS'//UTC time
- queries that are in progress during point in time update will complete against the version of data they were started against [1]
- {operation} rename snapshot
- {operation} delete snapshot
- via DELETE
- when the parent warehouse gets deleted, the snapshot is also deleted [1]
- {operation} modify source table
- DDL changes to source will only impact queries in the snapshot against tables affected [1]
- {operation} join multiple snapshots
- the resulting snapshot date will be applied to each warehouse connection [1]
- {operation} retrieve metadata
- via sys.databases [1]
- [permissions] inherited from the source warehouse [1]
- ⇐ any permission changes in the source warehouse applies instantly to the snapshot [1]
- security updates on source database will be rendered immediately to the snapshot databases [1]
- {limitation} can only be created against new warehouses [1]
- created after Mar-2025
- {limitation} do not appear in SSMS Object Explorer but will show up in the database selection dropdown [1]
- {limitation} datetime can be set to any date in the past up to 30 days or database creation time (whichever is later) [1]
- {limitation} modified objects after the snapshot timestamp become invalid in the snapshot [1]
- applies to tables, views, and stored procedures [1]
- {limitation} must be recreated if the data warehouse is restored [1]
- {limitation} aren’t supported on the SQL analytics endpoint of the Lakehouse [1]
- {limitation} aren’t supported as a source for OneLake shortcuts [1]
- [Power BI]{limitation} require Direct Query or Import mode [1]
- don’t support Direct Lake
References:
[1] Microsoft Learn (2025) Fabric: Warehouse Snapshots in Microsoft
Fabric (Preview) [link]
[2] Microsoft Learn (2025) Warehouse snapshots (preview) [link]
[3] Microsoft Learn (2025) Create and manage a warehouse snapshot (preview)
[link]
Resources:
Acronyms:
DDL - Data Definition Language
ETL - Extract, Transfer, Load
ETL - Extract, Transfer, Load
MF - Microsoft Fabric
SSMS - SQL Server Management Studio
SSMS - SQL Server Management Studio
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