DatriseAI-first ETL

Totango Amazon Redshift

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

How Datrise loads Totango into Amazon Redshift

Datrise syncs Totango's contacts, accounts, deals, activities, and lifecycle events 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

Totango: Customer success platform for health scores, playbooks, and renewals.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Totango entities map to Amazon Redshift

Totango entityAmazon Redshift objectNotes
contactstotango_contactsid PK · custom fields → SUPER columns
accountstotango_accountsid PK · linked to totango_contacts
dealstotango_dealsid PK · linked to totango_contacts
activitiestotango_activitiesTIMESTAMPTZ events

FAQ

How does Datrise handle Totango'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 Totango 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

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