DatriseAI-first ETL

Google Drive Amazon Redshift

AI-first ETL from Google Drive into Amazon Redshift. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Drive into Amazon Redshift

Datrise syncs Google Drive's files, folders, permissions, and revision metadata into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.

Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.

Ideal for AWS-native warehouses already using the Redshift ecosystem.

Endpoints

Google Drive: Cloud file storage often used for operational exports.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Google Drive entities map to Amazon Redshift

Google Drive entityAmazon Redshift objectNotes
filesgoogle_drive_filesid PK · custom fields → SUPER columns
foldersgoogle_drive_foldersid PK · linked to google_drive_files
permissionsgoogle_drive_permissionsid PK · linked to google_drive_files
revision metadatagoogle_drive_revision_metadataid PK · linked to google_drive_files

FAQ

How does Datrise handle Google Drive's custom fields in Amazon Redshift?

Flexible values are stored as SUPER columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon Redshift types.

How does the Google Drive to Amazon Redshift sync stay up to date?

It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.

Related pipelines

Early access

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