Azure Blob Storage is a cloud-based object storage service provided by Microsoft Azure. It allows users to store and manage unstructured data, such as documents, images, videos, and backups, in a highly scalable and secure manner, offering high durability, accessibility, and security and making it ideal for a wide range of applications and scenarios in the cloud.
Authorize Connection to Azure Blob Storage
Authorize the connection so Dataddo can write files to Azure Blob Storage:
Azure Blob Storage
| Field | Description |
|---|---|
| A name for this authorizer in Dataddo | A label so you can recognize the connection later. |
| Storage Account | Provide the name of Storage Account. Check Azure Portal and find Storage Account to get the value. |
| Container | Provide a name of the Container within the Storage Account you want to use for reading or writing the data. |
| Shared access token | Shared Access Token generated for the Container. Use the value in the format of Blob SAS Token. |
Microsoft Service Principal
| Field | Description |
|---|---|
| A name for this authorizer in Dataddo | A label so you can recognize the connection later. |
| Client ID | Client ID |
| Client Secret (Shared Key) | Client Secret (Shared Key) |
| Tenant ID | Tenant ID |
| Scopes | Select the permissions (scopes) required by the Microsoft service you are connecting to, as specified in its official API documentation. |
Dataddo validates the connection when you save it.
Create an Azure Blob Storage Destination
Go to Destinations, click Create Destination, and select Azure Blob Storage. Give the destination a name, choose the authorizer, then set:
| Field | Description |
|---|---|
| Storage Account Name | Storage Account Name |
| Container | Container |
| Path | Path |
Click Save.
Supported File Formats
Each flow run writes the data as a file in the format you pick.
| Format | Description |
|---|---|
csv |
Azure Blob Storage writes the data as CSV files. |
json |
Azure Blob Storage writes the data as JSON files. |
jsonl |
Azure Blob Storage writes the data as JSONL files. |
parquet |
Azure Blob Storage writes the data as PARQUET files. |
For CSV you can set the delimiter, header row, and date formatting. For Parquet, JSON, and JSONL you can set the timestamp unit.
File Naming
You can also build a custom filename with these placeholders (see Dynamic File Naming Patterns for the full list):
{{objectLabel}}and{{objectId}}: the flow name and id.{{today}}and{{yesterday}}: the run date.{{dateRangeStart}}and{{dateRangeEnd}}: the bounds of the flow's date range.- Date-range expressions such as
{{1d1}}(yesterday) or{{90d1}}(the last 90 days through yesterday). - Add a date format after a
|, for example{{today|Ymd}}gives20201231and{{1d1|Y-m-d}}gives2020-12-31.
File Partitioning
File partitioning splits a large dataset into smaller files based on a criterion such as date, which improves how a data lake organizes and queries the data (see Data Lake Ingestion). In Dataddo you partition by putting date variables from File Naming into the file name, so each flow run writes its own dated file.
For example, events_{{1d1|Y-m-d}}.parquet writes one Parquet file per day, so a lake engine such as Azure Blob Storage can read the set of files as a date-partitioned dataset. Pick a file format like Parquet or CSV that your lake reads, and schedule the flow to match the partition period (for example daily for a daily date token).
Write Modes
Each flow run writes a file at the resolved name. The default is truncate_insert: insert keeps writing new files, and truncate_insert replaces the file at the same name.
How Data Is Delivered
Every run produces one file at the resolved name. A date-stamped name accumulates a new snapshot file per run, which is the pattern described in Data Lake Ingestion.
How to Create a Flow to Azure Blob Storage
- Go to Flows and click Create Flow.
- Add one or more sources.
- Add Azure Blob Storage as the destination and pick the authorizer.
- Choose the file format and the file name.
- Set the schedule and click Save.
Troubleshooting
Cannot connect to Azure Blob Storage
Dataddo cannot reach Azure Blob Storage. Check the credentials, path, and permissions in the authorizer and destination, and make sure Azure Blob Storage is reachable by Dataddo.
File is not created
The account used by Dataddo lacks write permission on the target path. Grant write access to the folder or bucket and restart the flow.