DatriseAI-first ETL

Oracle Database to Amazon DynamoDB Integration

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

How Datrise loads Oracle Database into Amazon DynamoDB

Datrise syncs Oracle Database's tables, rows, schemas, indexes, sequences, and redo log changes into Amazon DynamoDB as an item per source record in a table per entity. Flexible or custom fields land in nested map/list attributes, and timestamps such as created, updated, and status changes are typed as ISO-8601 string or epoch number attributes.

Sync is incremental: Datrise uses PutItem/UpdateItem keyed on a partition key derived from the entity id, so re-runs update only what changed. Partition-key design on the entity id to spread throughput evenly. DynamoDB rewards access-pattern-first key design, so Datrise sets partition/sort keys from your entity ids rather than scan-heavy defaults.

Ideal for serverless apps needing single-digit-millisecond key lookups on CRM data.

Endpoints

Oracle Database: Oracle Database for enterprise transactional workloads.

Amazon DynamoDB: Serverless key-value and document store on AWS.

How Oracle Database entities map to Amazon DynamoDB

Oracle Database entityAmazon DynamoDB objectNotes
tablesoracle_db_tablesid PK · custom fields → nested map/list attributes
rowsoracle_db_rowsid PK · linked to oracle_db_tables
schemasoracle_db_schemasid PK · linked to oracle_db_tables
indexesoracle_db_indexesid PK · linked to oracle_db_tables

FAQ

How does Datrise handle Oracle Database's custom fields in Amazon DynamoDB?

Flexible values are stored as nested map/list attributes, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon DynamoDB types.

How does the Oracle Database to Amazon DynamoDB sync stay up to date?

It runs incrementally — Datrise uses PutItem/UpdateItem keyed on a partition key derived from the entity id.

Related pipelines

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