DatriseAI-first ETL

Pendo Neon

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

How Datrise loads Pendo into Neon

Datrise syncs Pendo's events, guides, NPS, feature adoption, and account metadata into Neon as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative partitioning by load date. Neon separates compute from storage, so Datrise batches writes to keep autoscaling compute from cold-starting on every small change.

Ideal for serverless Postgres workloads that scale to zero between syncs.

Endpoints

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

Neon: Serverless Postgres destination with branching and autoscaling.

How Pendo entities map to Neon

Pendo entityNeon 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 Neon?

Flexible values are stored as jsonb columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Neon types.

How does the Pendo to Neon sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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