DatriseAI-first ETL

Oracle CX Amazon S3 Data Lake

AI-first ETL from Oracle CX into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.

How Datrise loads Oracle CX into Amazon S3 Data Lake

Datrise syncs Oracle CX's enterprise CX entities across sales, service, and customer operations 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

Oracle CX: Enterprise customer experience suite with sales and service data.

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

How Oracle CX entities map to Amazon S3 Data Lake

Oracle CX entityAmazon S3 Data Lake objectNotes
enterprise CX entities across salesoracle_cx_enterprise_cx_entities_across_salesid PK · custom fields → nested struct/map fields in Parquet
serviceoracle_cx_serviceid PK · linked to oracle_cx_enterprise_cx_entities_across_sales
customer operationsoracle_cx_customer_operationsid PK · linked to oracle_cx_enterprise_cx_entities_across_sales

FAQ

How does Datrise handle Oracle CX'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 Oracle CX 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

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