DatriseAI-first ETL

Parquet File to Oracle Database Integration

AI-first ETL from Parquet File into Oracle Database. Governed entities, incremental sync, typed landing tables.

How Datrise loads Parquet File into Oracle Database

Datrise syncs Parquet File's row groups, columns, schemas, partitions, file batches, and column statistics into Oracle Database as a typed table per source entity. Flexible or custom fields land in JSON or CLOB columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses a watermark on updated-at, applied with MERGE INTO, so re-runs update only what changed. Optional range partitioning by load date. Oracle treats an empty string as NULL, so Datrise distinguishes blank source values from missing ones during load.

Ideal for enterprise data teams consolidating CRM data into an Oracle warehouse.

Endpoints

Parquet File: Columnar Parquet files from lakes and exports.

Oracle Database: Enterprise RDBMS with advanced partitioning and HA.

How Parquet File entities map to Oracle Database

Parquet File entityOracle Database objectNotes
row groupsparquet_file_row_groupsid PK · custom fields → JSON or CLOB columns
columnsparquet_file_columnsid PK · linked to parquet_file_row_groups
schemasparquet_file_schemasid PK · linked to parquet_file_row_groups
partitionsparquet_file_partitionsid PK · linked to parquet_file_row_groups

FAQ

How does Datrise handle Parquet File's custom fields in Oracle Database?

Flexible values are stored as JSON or CLOB columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Oracle Database types.

How does the Parquet File to Oracle Database sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with MERGE INTO.

Related pipelines

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