Share and schedule data sharing using Azure Data Share
Azure Data Share offers two ways to share your data:
- Snapshot-based sharing
- In-place sharing
Snapshot-based sharing
When you, as a data provider, set up a snapshot-based share, the data moves from your Azure subscription to the data consumer's Azure subscription, through an invitation sent to the recipients' email. Once they accept the invitation, it triggers a full snapshot of the dataset that you shared with them, and is a point-in-time representation of the shared data.
Once the data is accepted, it lands in their storage account and can receive regular, incremental updates to sync with the latest version of the data.
The incremental updates of the data that you shared, can be scheduled through a snapshot schedule on an hourly or daily basis. The data consumer has to subscribe to this snapshot schedule. Therefore, if your data changes regularly, and the data consumer needs to have the most recent data, this snapshot-based sharing might be an option.
The Azure Data platform services that currently support snapshot-based sharing are:
- Azure Synapse Analytics
- Azure SQL Database
- Azure Blob Storage
- Azure Data Lake Storage (Gen1 and Gen2)
- Azure Data Explorer
In the case of sharing from SQL-based sources, the data consumer can also choose whether they receive data in Parquet or CSV.
In-place sharing
When data providers use in-place sharing, data won't be copied and resides where it's stored in the data provider's Azure subscription. Once in-place sharing is set up by the data provider through the invitation flow, a symbolic link between a data provider's source data store and the data consumer's target data store is created. This enables the data consumer to read and query data using its target data store. Any changes in the data providers source data store, is immediately available to the data consumer to read and query.
Note
In-place sharing is currently in preview for Azure Data Explorer.
Now that you understand the Azure Data Share sharing methods, in the next unit let’s start sharing data with Azure Data Share.