Meta Ads → Snowflake
AI-first ETL from Meta Ads into Snowflake. Governed entities, incremental sync, typed landing tables.
How Datrise loads Meta Ads into Snowflake
Datrise syncs Meta Ads's campaign spend, impressions, clicks, conversions, and audience segments 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
Meta Ads: Facebook and Instagram ad source for spend and engagement.
Snowflake: Cloud data warehouse with separated compute and storage.
How Meta Ads entities map to Snowflake
| Meta Ads entity | Snowflake object | Notes |
|---|---|---|
| campaign spend | meta_ads_campaign_spend | id PK · custom fields → VARIANT columns |
| impressions | meta_ads_impressions | id PK · linked to meta_ads_campaign_spend |
| clicks | meta_ads_clicks | id PK · linked to meta_ads_campaign_spend |
| conversions | meta_ads_conversions | id PK · linked to meta_ads_campaign_spend |
FAQ
How does Datrise handle Meta 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 Meta 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
More destinations for Meta Ads
Early access
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