DatriseAI-first ETL

Google Ecommerce MySQL

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

How Datrise loads Google Ecommerce into MySQL

Datrise syncs Google Ecommerce's records, events, and configuration objects into MySQL as a typed table per source entity. Flexible or custom fields land in JSON columns, and timestamps such as created, updated, and status changes are typed as DATETIME/TIMESTAMP.

Sync is incremental: Datrise uses a watermark on updated-at, applied with INSERT … ON DUPLICATE KEY UPDATE, so re-runs update only what changed. Optional RANGE partitioning by load date. MySQL collation matters for CRM text, so Datrise lands utf8mb4 to preserve emoji and non-Latin characters.

Ideal for operational reporting and app databases already standardized on MySQL.

Endpoints

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

MySQL: Widely used OSS relational engine (InnoDB).

How Google Ecommerce entities map to MySQL

Google Ecommerce entityMySQL objectNotes
recordsgoogle_ecommerce_recordsid PK · custom fields → JSON columns
eventsgoogle_ecommerce_eventsDATETIME/TIMESTAMP events
configuration objectsgoogle_ecommerce_configuration_objectsid PK · linked to google_ecommerce_records

FAQ

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

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

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

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

Related pipelines

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