DatriseAI-first ETL

Amazon RDS to MicroStrategy Integration

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

How Datrise loads Amazon RDS into MicroStrategy

Datrise syncs Amazon RDS's tables, rows, schemas, indexes, primary keys, and change streams 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 RDS: Managed relational database service on AWS.

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

How Amazon RDS entities map to MicroStrategy

Amazon RDS entityMicroStrategy objectNotes
tablesamazon_rds_tablesid PK · custom fields → flattened columns
rowsamazon_rds_rowsid PK · linked to amazon_rds_tables
schemasamazon_rds_schemasid PK · linked to amazon_rds_tables
indexesamazon_rds_indexesid PK · linked to amazon_rds_tables

FAQ

How does Datrise handle Amazon RDS'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 RDS to MicroStrategy sync stay up to date?

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

Related pipelines

Early access

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