DatriseAI-first ETL

Amazon DynamoDB to MicroStrategy Integration

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

How Datrise loads Amazon DynamoDB into MicroStrategy

Datrise syncs Amazon DynamoDB's tables, items, partition keys, sort keys, attributes, and stream records into MicroStrategy as warehouse tables for MicroStrategy's schema objects. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the warehouse tables behind attributes and metrics, so re-runs update only what changed. Date-partitioned facts. MicroStrategy maps attributes to columns, so Datrise lands stable keys and names so metrics don't break.

Ideal for large-scale enterprise reporting and governance.

Endpoints

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

MicroStrategy: Enterprise BI with dossiers, governed metrics, and mobility.

How Amazon DynamoDB entities map to MicroStrategy

Amazon DynamoDB entityMicroStrategy objectNotes
tablessource_dynamodb_tablesid PK · custom fields → flattened columns
itemssource_dynamodb_itemsid PK · linked to source_dynamodb_tables
partition keyssource_dynamodb_partition_keysid PK · linked to source_dynamodb_tables
sort keyssource_dynamodb_sort_keysid PK · linked to source_dynamodb_tables

FAQ

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

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

How does the Amazon DynamoDB to MicroStrategy sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the warehouse tables behind attributes and metrics.

Related pipelines

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