> For the complete documentation index, see [llms.txt](https://docs.roboflow.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.roboflow.com/datasets/adding-data/upload-data-from-aws-gcp-and-azure.md).

# Import Data from Cloud Providers

Cloud storage solutions like AWS S3, Azure Blob Storage, and Google Cloud Storage offer highly scalable and secure options for storing large volumes of image data. These platforms have made it increasingly convenient to manage and access data for various applications. When it comes to streamlining the data pipeline for computer vision models, Roboflow can seamlessly integrate with these cloud storage services.

If you use AWS S3 and want images to sync automatically on a continuous basis, use [Datasources](/datasets/adding-data/datasources.md) instead. Datasources mirror your bucket into the Roboflow asset library without any scripting required.

The scripted options below are suited for one-time or ad-hoc uploads, or for Azure Blob Storage and Google Cloud Storage where automatic sync is not yet available.

{% content-ref url="/pages/L5e7NPoLQMu37Yyg3wRE" %}
[AWS S3 Bucket](/datasets/adding-data/upload-data-from-aws-gcp-and-azure/aws-s3-bucket.md)
{% endcontent-ref %}

{% content-ref url="/pages/ONs4rB28xzISHHV4S2Xk" %}
[Azure Blob Storage](/datasets/adding-data/upload-data-from-aws-gcp-and-azure/azure-blob-storage.md)
{% endcontent-ref %}

{% content-ref url="/pages/3o3L7KAgHMRZ180rRguZ" %}
[Google Cloud Storage](/datasets/adding-data/upload-data-from-aws-gcp-and-azure/google-cloud-storage.md)
{% endcontent-ref %}