DatriseAI-first ETL

Redshift to Amazon DynamoDB Integration

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

How Datrise loads Redshift into Amazon DynamoDB

Datrise syncs Redshift's tables, rows, schemas, sort keys, distribution keys, 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

Redshift: Columnar cloud data warehouse on AWS.

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

How Redshift entities map to Amazon DynamoDB

Redshift entityAmazon DynamoDB objectNotes
tablesredshift_tablesid PK · custom fields → nested map/list attributes
rowsredshift_rowsid PK · linked to redshift_tables
schemasredshift_schemasid PK · linked to redshift_tables
sort keysredshift_sort_keysid PK · linked to redshift_tables

FAQ

How does Datrise handle Redshift'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 Redshift 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

Early access

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