SAP Fieldglass to Amazon S3 Data Lake Integration
AI-first ETL from SAP Fieldglass into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.
How Datrise loads SAP Fieldglass into Amazon S3 Data Lake
Datrise syncs SAP Fieldglass's workers, job postings, work orders, time sheets, suppliers, and invoices 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
SAP Fieldglass: External workforce and contingent labor management.
Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.
How SAP Fieldglass entities map to Amazon S3 Data Lake
| SAP Fieldglass entity | Amazon S3 Data Lake object | Notes |
|---|---|---|
| workers | sap_fieldglass_workers | id PK · custom fields → nested struct/map fields in Parquet |
| job postings | sap_fieldglass_job_postings | id PK · linked to sap_fieldglass_workers |
| work orders | sap_fieldglass_work_orders | id PK · linked to sap_fieldglass_workers |
| time sheets | sap_fieldglass_time_sheets | id PK · linked to sap_fieldglass_workers |
FAQ
How does Datrise handle SAP Fieldglass'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 SAP Fieldglass 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 SAP Fieldglass
- SAP Fieldglass → Azure Data Lake Storage
- SAP Fieldglass → Azure Synapse
- SAP Fieldglass → Spreadsheets
- SAP Fieldglass → Airtable
- SAP Fieldglass → CSV Files
- SAP Fieldglass → MongoDB
- SAP Fieldglass → Supabase
- SAP Fieldglass → Neon
- SAP Fieldglass → PlanetScale
- SAP Fieldglass → Amazon DynamoDB
- SAP Fieldglass → Looker
- SAP Fieldglass → Looker Studio
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Early access
Connect SAP Fieldglass to Amazon S3 Data Lake the easy way
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