Google Analytics 360 → Amazon S3 Data Lake
AI-first ETL from Google Analytics 360 into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.
How Datrise loads Google Analytics 360 into Amazon S3 Data Lake
Datrise syncs Google Analytics 360's records, events, and configuration objects 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 360: SaaS or API data source for analytics and warehouse sync.
Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.
How Google Analytics 360 entities map to Amazon S3 Data Lake
| Google Analytics 360 entity | Amazon S3 Data Lake object | Notes |
|---|---|---|
| records | google_analytics_360_records | id PK · custom fields → nested struct/map fields in Parquet |
| events | google_analytics_360_events | ISO-8601 timestamp columns events |
| configuration objects | google_analytics_360_configuration_objects | id PK · linked to google_analytics_360_records |
FAQ
How does Datrise handle Google Analytics 360'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 360 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 360
- Google Analytics 360 → Azure Data Lake Storage
- Google Analytics 360 → Azure Synapse
- Google Analytics 360 → Spreadsheets
- Google Analytics 360 → Airtable
- Google Analytics 360 → CSV Files
- Google Analytics 360 → MongoDB
- Google Analytics 360 → Supabase
- Google Analytics 360 → Neon
- Google Analytics 360 → PlanetScale
- Google Analytics 360 → Amazon DynamoDB
- Google Analytics 360 → Looker
- Google Analytics 360 → Looker Studio
More sources for Amazon S3 Data Lake
- Google Cloud SQL → Amazon S3 Data Lake
- Google Cloud SQL Postgresql → Amazon S3 Data Lake
- Google Cloud Storage F → Amazon S3 Data Lake
- Google Directory → Amazon S3 Data Lake
- Google Ecommerce → Amazon S3 Data Lake
- Google Pagespeed Insights → Amazon S3 Data Lake
- Google Webfonts → Amazon S3 Data Lake
- Greenhouse → Amazon S3 Data Lake
- Gridly → Amazon S3 Data Lake
- Gutendex → Amazon S3 Data Lake
- Harness → Amazon S3 Data Lake
- Harvest Forecast → Amazon S3 Data Lake
Early access
Connect Google Analytics 360 to Amazon S3 Data Lake the easy way
Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.