Google Analytics 4 to Amazon S3 Data Lake Integration
AI-first ETL from Google Analytics 4 into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Analytics 4 into Amazon S3 Data Lake
Datrise syncs Google Analytics 4's events, users, sessions, traffic sources, conversions, and audiences into Amazon S3 Data Lake as columnar Parquet objects partitioned per source entity. Flexible or custom fields land in nested struct/map fields in Parquet, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.
Sync is incremental: Datrise uses writes new date partitions and compacts small files on a schedule, so re-runs update only what changed. Hive-style path partitioning (entity/date) for engine-agnostic reads. A lake has no schema enforcement, so Datrise writes a schema manifest alongside the data to keep downstream engines consistent.
Ideal for an open, engine-neutral storage layer for Spark, Athena, Trino, or DuckDB.
Endpoints
Google Analytics 4: Event-based web and app analytics from Google.
Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.
How Google Analytics 4 entities map to Amazon S3 Data Lake
| Google Analytics 4 entity | Amazon S3 Data Lake object | Notes |
|---|---|---|
| events | ga4_events | ISO-8601 timestamp columns 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 Amazon S3 Data Lake?
Flexible values are stored as nested struct/map fields in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon S3 Data Lake types.
How does the Google Analytics 4 to Amazon S3 Data Lake sync stay up to date?
It runs incrementally — Datrise uses writes new date partitions and compacts small files on a schedule.
Related pipelines
More destinations for Google Analytics 4
- Google Analytics 4 → Azure Data Lake Storage
- Google Analytics 4 → Azure Synapse
- Google Analytics 4 → Spreadsheets
- Google Analytics 4 → Airtable
- Google Analytics 4 → CSV Files
- Google Analytics 4 → MongoDB
- Google Analytics 4 → Supabase
- Google Analytics 4 → Neon
- Google Analytics 4 → PlanetScale
- Google Analytics 4 → Amazon DynamoDB
- Google Analytics 4 → Looker
- Google Analytics 4 → Looker Studio
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Early access
Connect Google Analytics 4 to Amazon S3 Data Lake the easy way
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