DatriseAI-first ETL

Google Ads Snowflake

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

How Datrise loads Google Ads into Snowflake

Datrise syncs Google Ads's campaigns, ad groups, spend, clicks, conversions, and attribution signals into Snowflake as a typed table per source entity. Flexible or custom fields land in VARIANT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP_TZ.

Sync is incremental: Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size, so re-runs update only what changed. Automatic micro-partitioning, with optional clustering keys on high-cardinality ids. Snowflake upper-cases unquoted identifiers, so Datrise standardizes on lower-case quoted names to keep column references stable.

Ideal for central analytics warehouses feeding BI and AI workloads.

Endpoints

Google Ads: Paid media source for campaign and conversion metrics.

Snowflake: Cloud data warehouse with separated compute and storage.

How Google Ads entities map to Snowflake

Google Ads entitySnowflake objectNotes
campaignsgoogle_ads_campaignsid PK · custom fields → VARIANT columns
ad groupsgoogle_ads_ad_groupsid PK · linked to google_ads_campaigns
spendgoogle_ads_spendid PK · linked to google_ads_campaigns
clicksgoogle_ads_clicksid PK · linked to google_ads_campaigns

FAQ

How does Datrise handle Google Ads's custom fields in Snowflake?

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

How does the Google Ads to Snowflake sync stay up to date?

It runs incrementally — Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size.

Related pipelines

Early access

Connect Google Ads to Snowflake the easy way

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