DatriseAI-first ETL

Google Analytics 360 Amazon Redshift

AI-first ETL from Google Analytics 360 into Amazon Redshift. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Analytics 360 into Amazon Redshift

Datrise syncs Google Analytics 360's records, events, and configuration objects 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 Analytics 360: SaaS or API data source for analytics and warehouse sync.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Google Analytics 360 entities map to Amazon Redshift

Google Analytics 360 entityAmazon Redshift objectNotes
recordsgoogle_analytics_360_recordsid PK · custom fields → SUPER columns
eventsgoogle_analytics_360_eventsTIMESTAMPTZ events
configuration objectsgoogle_analytics_360_configuration_objectsid PK · linked to google_analytics_360_records

FAQ

How does Datrise handle Google Analytics 360'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 Analytics 360 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

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