Adobe Commerce (Magento) → Amazon S3 Data Lake
AI-first ETL from Adobe Commerce (Magento) into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.
How Datrise loads Adobe Commerce (Magento) into Amazon S3 Data Lake
Datrise syncs Adobe Commerce (Magento)'s orders, products, customers, carts, and store views 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
Adobe Commerce (Magento): Enterprise e-commerce catalog, orders, and customer data.
Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.
How Adobe Commerce (Magento) entities map to Amazon S3 Data Lake
| Adobe Commerce (Magento) entity | Amazon S3 Data Lake object | Notes |
|---|---|---|
| orders | magento_orders | id PK · custom fields → nested struct/map fields in Parquet |
| products | magento_products | id PK · linked to magento_orders |
| customers | magento_customers | id PK · linked to magento_orders |
| carts | magento_carts | id PK · linked to magento_orders |
FAQ
How does Datrise handle Adobe Commerce (Magento)'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 Adobe Commerce (Magento) 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 Adobe Commerce (Magento)
- Adobe Commerce (Magento) → Azure Data Lake Storage
- Adobe Commerce (Magento) → Azure Synapse
- Adobe Commerce (Magento) → Spreadsheets
- Adobe Commerce (Magento) → Airtable
- Adobe Commerce (Magento) → CSV Files
- Adobe Commerce (Magento) → MongoDB
- Adobe Commerce (Magento) → Supabase
- Adobe Commerce (Magento) → Neon
- Adobe Commerce (Magento) → PlanetScale
- Adobe Commerce (Magento) → Amazon DynamoDB
- Adobe Commerce (Magento) → Looker
- Adobe Commerce (Magento) → Looker Studio
More sources for Amazon S3 Data Lake
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- RingCentral → Amazon S3 Data Lake
- Segment → Amazon S3 Data Lake
- Square → Amazon S3 Data Lake
- Stripe → Amazon S3 Data Lake
- SurveyMonkey → Amazon S3 Data Lake
Early access
Connect Adobe Commerce (Magento) 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.