Google Analytics 4 to Snowflake Integration

AI-first ETL from Google Analytics 4 into Snowflake. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Analytics 4 into Snowflake

Datrise syncs Google Analytics 4's events, users, sessions, traffic sources, conversions, and audiences 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 Analytics 4: Event-based web and app analytics from Google.

Snowflake: Cloud data warehouse with separated compute and storage.

How Google Analytics 4 entities map to Snowflake

Google Analytics 4 entity	Snowflake object	Notes
events	`ga4_events`	TIMESTAMP_TZ events
users	`ga4_users`	id PK · linked to ga4_events
sessions	`ga4_sessions`	id PK · linked to ga4_events
traffic sources	`ga4_traffic_sources`	id PK · linked to ga4_events

FAQ

How does Datrise handle Google Analytics 4'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 Analytics 4 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.

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Early access

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