Google Ads → MongoDB
AI-first ETL from Google Ads into MongoDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Ads into MongoDB
Datrise syncs Google Ads's campaigns, ad groups, spend, clicks, conversions, and attribution signals into MongoDB as a collection per source entity. Flexible or custom fields land in native nested documents, and timestamps such as created, updated, and status changes are typed as BSON Date.
Sync is incremental: Datrise uses upserts by stable id with updateOne(upsert) on the source primary key, so re-runs update only what changed. Optional sharding on the entity id for large collections. Mongo has no fixed schema, so Datrise keeps field types consistent across documents to avoid mixed-type query surprises.
Ideal for document-oriented apps that want CRM data in their existing Mongo store.
Endpoints
Google Ads: Paid media source for campaign and conversion metrics.
MongoDB: Document database for flexible schemas.
How Google Ads entities map to MongoDB
| Google Ads entity | MongoDB object | Notes |
|---|---|---|
| campaigns | google_ads_campaigns | id PK · custom fields → native nested documents |
| ad groups | google_ads_ad_groups | id PK · linked to google_ads_campaigns |
| spend | google_ads_spend | id PK · linked to google_ads_campaigns |
| clicks | google_ads_clicks | id PK · linked to google_ads_campaigns |
FAQ
How does Datrise handle Google Ads's custom fields in MongoDB?
Flexible values are stored as native nested documents, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native MongoDB types.
How does the Google Ads to MongoDB sync stay up to date?
It runs incrementally — Datrise uses upserts by stable id with updateOne(upsert) on the source primary key.
Related pipelines
More destinations for Google Ads
Early access
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