DatriseAI-first ETL

Salesloft Amazon Redshift

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

How Datrise loads Salesloft into Amazon Redshift

Datrise syncs Salesloft's cadence activity, conversation signals, and revenue workflow execution 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

Salesloft: Revenue workflow platform for cadences, conversations, and coaching signals.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Salesloft entities map to Amazon Redshift

Salesloft entityAmazon Redshift objectNotes
cadence activitysalesloft_cadence_activityTIMESTAMPTZ events
conversation signalssalesloft_conversation_signalsid PK · linked to salesloft_cadence_activity
revenue workflow executionsalesloft_revenue_workflow_executionid PK · linked to salesloft_cadence_activity

FAQ

How does Datrise handle Salesloft'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 Salesloft 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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