Salesforce Commerce Cloud to Amazon S3 Data Lake Integration
AI-first ETL from Salesforce Commerce Cloud into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.
How Datrise loads Salesforce Commerce Cloud into Amazon S3 Data Lake
Datrise syncs Salesforce Commerce Cloud's orders, products, customers, baskets, promotions, and inventory records 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
Salesforce Commerce Cloud: Salesforce storefront, catalog, and order management.
Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.
How Salesforce Commerce Cloud entities map to Amazon S3 Data Lake
| Salesforce Commerce Cloud entity | Amazon S3 Data Lake object | Notes |
|---|---|---|
| orders | salesforce_commerce_cloud_orders | id PK · custom fields → nested struct/map fields in Parquet |
| products | salesforce_commerce_cloud_products | id PK · linked to salesforce_commerce_cloud_orders |
| customers | salesforce_commerce_cloud_customers | id PK · linked to salesforce_commerce_cloud_orders |
| baskets | salesforce_commerce_cloud_baskets | id PK · linked to salesforce_commerce_cloud_orders |
FAQ
How does Datrise handle Salesforce Commerce Cloud'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 Salesforce Commerce Cloud 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 Salesforce Commerce Cloud
- Salesforce Commerce Cloud → Azure Data Lake Storage
- Salesforce Commerce Cloud → Azure Synapse
- Salesforce Commerce Cloud → Spreadsheets
- Salesforce Commerce Cloud → Airtable
- Salesforce Commerce Cloud → CSV Files
- Salesforce Commerce Cloud → MongoDB
- Salesforce Commerce Cloud → Supabase
- Salesforce Commerce Cloud → Neon
- Salesforce Commerce Cloud → PlanetScale
- Salesforce Commerce Cloud → Amazon DynamoDB
- Salesforce Commerce Cloud → Looker
- Salesforce Commerce Cloud → Looker Studio
More sources for Amazon S3 Data Lake
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- Twenty CRM → Amazon S3 Data Lake
- Maximizer CRM → Amazon S3 Data Lake
- Method:CRM → Amazon S3 Data Lake
- EngageBay → Amazon S3 Data Lake
- Megaplan → Amazon S3 Data Lake
Early access
Connect Salesforce Commerce Cloud to Amazon S3 Data Lake the easy way
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