DatriseAI-first ETL

Google Ecommerce Neon

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

How Datrise loads Google Ecommerce into Neon

Datrise syncs Google Ecommerce'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

Google Ecommerce: SaaS or API data source for analytics and warehouse sync.

Neon: Serverless Postgres destination with branching and autoscaling.

How Google Ecommerce entities map to Neon

Google Ecommerce entityNeon objectNotes
recordsgoogle_ecommerce_recordsid PK · custom fields → jsonb columns
eventsgoogle_ecommerce_eventstimestamptz events
configuration objectsgoogle_ecommerce_configuration_objectsid PK · linked to google_ecommerce_records

FAQ

How does Datrise handle Google Ecommerce'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 Google Ecommerce 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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