DatriseAI-first ETL

Sap Fieldglass Amazon S3 Data Lake

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 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

Sap Fieldglass: SaaS or API data source for analytics and warehouse sync.

Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.

How Sap Fieldglass entities map to Amazon S3 Data Lake

Sap Fieldglass entityAmazon S3 Data Lake objectNotes
recordssap_fieldglass_recordsid PK · custom fields → nested struct/map fields in Parquet
eventssap_fieldglass_eventsISO-8601 timestamp columns events
configuration objectssap_fieldglass_configuration_objectsid PK · linked to sap_fieldglass_records

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

Early access

Connect Sap Fieldglass 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.