DatriseAI-first ETL

Teradata to Amazon DynamoDB Integration

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

How Datrise loads Teradata into Amazon DynamoDB

Datrise syncs Teradata's tables, rows, schemas, indexes, primary indexes, and query history 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

Teradata: Teradata analytical database for enterprise workloads.

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

How Teradata entities map to Amazon DynamoDB

Teradata entityAmazon DynamoDB objectNotes
tablesteradata_d_tablesid PK · custom fields → nested map/list attributes
rowsteradata_d_rowsid PK · linked to teradata_d_tables
schemasteradata_d_schemasid PK · linked to teradata_d_tables
indexesteradata_d_indexesid PK · linked to teradata_d_tables

FAQ

How does Datrise handle Teradata'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 Teradata 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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