Google Ecommerce to PostgreSQL Integration

How Datrise loads Google Ecommerce into PostgreSQL

Datrise syncs Google Ecommerce's transactions, products, product impressions, checkout steps, revenue, and refunds into PostgreSQL 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 each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Google Ecommerce: Ecommerce reporting from Google Analytics.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Google Ecommerce entities map to PostgreSQL

Google Ecommerce entity	PostgreSQL object	Notes
transactions	`google_ecommerce_transactions`	id PK · custom fields → jsonb columns
products	`google_ecommerce_products`	id PK · linked to google_ecommerce_transactions
product impressions	`google_ecommerce_product_impressions`	id PK · linked to google_ecommerce_transactions
checkout steps	`google_ecommerce_checkout_steps`	id PK · linked to google_ecommerce_transactions

FAQ

How does Datrise handle Google Ecommerce's custom fields in PostgreSQL?

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 PostgreSQL types.

How does the Google Ecommerce to PostgreSQL sync stay up to date?

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

Related pipelines

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