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On-premise users: click in-app to access the full platform documentation for your version of DataRobot.

AWS S3

Self-Managed AI Platform installations

The S3 connector will be automatically installed and does not need to be manually added.

Supported authentication

  • AWS credentials: Long-term credentials using aws_access_key_id and aws_secret_access_key.
  • AWS temporary credentials: Short-term credentials using aws_access_key_id, aws_secret_access_key, and aws_session_token.

Prerequisites

The following is required before connecting to AWS S3 in DataRobot:

  • AWS S3 account

Required parameters

The table below lists the minimum required fields to establish a connection with AWS S3:

Required field Description Documentation
bucketName A container that stores your data in AWS S3. AWS documentation

Note that you can specify bucketRegion under Show advanced options, however this parameter is not required.

Feature considerations

  • This connector does not support:

    • Feature Discovery projects
    • Data wrangling in Workbench
    • Adding dynamic datasets to a Workbench Use Case
  • This connector does support:

    • Creating and sharing AWS credentials using secure configurations.
    • Parquet file ingest including, single parquet files, partitioned parquet files in a folder, and zipped parquet files.

Updated April 4, 2024