DatriseAI-first ETL

Amazon Seller Partner Neon

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

How Datrise loads Amazon Seller Partner into Neon

Datrise syncs Amazon Seller Partner's records, events, and configuration objects 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

Amazon Seller Partner: SaaS or API data source for analytics and warehouse sync.

Neon: Serverless Postgres destination with branching and autoscaling.

How Amazon Seller Partner entities map to Neon

Amazon Seller Partner entityNeon objectNotes
recordsamazon_seller_partner_recordsid PK · custom fields → jsonb columns
eventsamazon_seller_partner_eventstimestamptz events
configuration objectsamazon_seller_partner_configuration_objectsid PK · linked to amazon_seller_partner_records

FAQ

How does Datrise handle Amazon Seller Partner'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 Amazon Seller Partner 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

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