DatriseAI-first ETL

Pendo Amazon Redshift

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

How Datrise loads Pendo into Amazon Redshift

Datrise syncs Pendo's events, guides, NPS, feature adoption, and account metadata 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

Pendo: Product analytics and in-app guidance for SaaS teams.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Pendo entities map to Amazon Redshift

Pendo entityAmazon Redshift objectNotes
eventspendo_eventsTIMESTAMPTZ events
guidespendo_guidesid PK · linked to pendo_events
NPSpendo_npsid PK · linked to pendo_events
feature adoptionpendo_feature_adoptionid PK · linked to pendo_events

FAQ

How does Datrise handle Pendo'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 Pendo 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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