DatriseAI-first ETL

Close Amazon Redshift

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

How Datrise loads Close into Amazon Redshift

Datrise syncs Close's leads, opportunities, calls, SMS events, and sequence performance 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

Close: Inside-sales CRM with calling and sequences.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Close entities map to Amazon Redshift

Close entityAmazon Redshift objectNotes
leadsclose_leadsid PK · custom fields → SUPER columns
opportunitiesclose_opportunitiesid PK · linked to close_leads
callsclose_callsid PK · linked to close_leads
SMS eventsclose_sms_eventsTIMESTAMPTZ events

FAQ

How does Datrise handle Close'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 Close 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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