Oracle Database to Amazon S3 Data Lake Integration
AI-first ETL from Oracle Database into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.
How Datrise loads Oracle Database into Amazon S3 Data Lake
Datrise syncs Oracle Database's tables, rows, schemas, indexes, sequences, and redo log changes 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 Database: Oracle Database for enterprise transactional workloads.
Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.
How Oracle Database entities map to Amazon S3 Data Lake
| Oracle Database entity | Amazon S3 Data Lake object | Notes |
|---|---|---|
| tables | oracle_db_tables | id PK · custom fields → nested struct/map fields in Parquet |
| rows | oracle_db_rows | id PK · linked to oracle_db_tables |
| schemas | oracle_db_schemas | id PK · linked to oracle_db_tables |
| indexes | oracle_db_indexes | id PK · linked to oracle_db_tables |
FAQ
How does Datrise handle Oracle Database'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 Database 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 Oracle Database
- Oracle Database → Azure Data Lake Storage
- Oracle Database → Azure Synapse
- Oracle Database → Spreadsheets
- Oracle Database → Airtable
- Oracle Database → CSV Files
- Oracle Database → MongoDB
- Oracle Database → Supabase
- Oracle Database → Neon
- Oracle Database → PlanetScale
- Oracle Database → Amazon DynamoDB
- Oracle Database → Looker
- Oracle Database → Looker Studio
More sources for Amazon S3 Data Lake
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Early access
Connect Oracle Database to Amazon S3 Data Lake the easy way
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