Google Ads → Redash
AI-first ETL from Google Ads into Redash. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Ads into Redash
Datrise syncs Google Ads's campaigns, ad groups, spend, clicks, conversions, and attribution signals into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.
Ideal for lightweight, query-driven dashboards.
Endpoints
Google Ads: Paid media source for campaign and conversion metrics.
Redash: Open-source SQL client for queries, visualizations, and dashboards.
How Google Ads entities map to Redash
| Google Ads entity | Redash object | Notes |
|---|---|---|
| campaigns | google_ads_campaigns | id PK · custom fields → flattened columns for query results |
| 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 Redash?
Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.
How does the Google Ads to Redash sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Google Ads
Early access
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