DatriseAI-first ETL

Salesflare Amazon Redshift

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

How Datrise loads Salesflare into Amazon Redshift

Datrise syncs Salesflare's B2B account intelligence, interactions, and automated relationship timelines 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

Salesflare: B2B CRM focused on automation and relationship timeline data.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Salesflare entities map to Amazon Redshift

Salesflare entityAmazon Redshift objectNotes
B2B account intelligencesalesflare_b2b_account_intelligenceid PK · custom fields → SUPER columns
interactionssalesflare_interactionsid PK · linked to salesflare_b2b_account_intelligence
automated relationship timelinessalesflare_automated_relationship_timelinesTIMESTAMPTZ events

FAQ

How does Datrise handle Salesflare'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 Salesflare 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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