Ga4 → Amazon Redshift
AI-first ETL from Ga4 into Amazon Redshift. Governed entities, incremental sync, typed landing tables.
How Datrise loads Ga4 into Amazon Redshift
Datrise syncs Ga4'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
Ga4: SaaS or API data source for analytics and warehouse sync.
Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.
How Ga4 entities map to Amazon Redshift
| Ga4 entity | Amazon Redshift object | Notes |
|---|---|---|
| records | ga4_records | id PK · custom fields → SUPER columns |
| events | ga4_events | TIMESTAMPTZ events |
| configuration objects | ga4_configuration_objects | id PK · linked to ga4_records |
FAQ
How does Datrise handle Ga4'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 Ga4 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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- Google Directory → Amazon Redshift
Early access
Connect Ga4 to Amazon Redshift the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.