DatriseAI-first ETL

Adjust Amazon Redshift

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

How Datrise loads Adjust into Amazon Redshift

Datrise syncs Adjust'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

Adjust: SaaS or API data source for analytics and warehouse sync.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Adjust entities map to Amazon Redshift

Adjust entityAmazon Redshift objectNotes
recordsadjust_recordsid PK · custom fields → SUPER columns
eventsadjust_eventsTIMESTAMPTZ events
configuration objectsadjust_configuration_objectsid PK · linked to adjust_records

FAQ

How does Datrise handle Adjust'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 Adjust 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

Connect Adjust 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.