DatriseAI-first ETL

PostgreSQL to Microsoft Power BI Integration

AI-first ETL from PostgreSQL into Microsoft Power BI. Governed entities, incremental sync, typed landing tables.

How Datrise loads PostgreSQL into Microsoft Power BI

Datrise syncs PostgreSQL's tables, rows, schemas, indexes, sequences, and replication slots into Microsoft Power BI as star-schema-friendly tables for an Import or DirectQuery dataset. Flexible or custom fields land in flattened columns (nested fields expanded), and timestamps such as created, updated, and status changes are typed as date/time columns with a date table.

Sync is incremental: Datrise uses incremental-refresh windows aligned to Power BI's RangeStart/RangeEnd, so re-runs update only what changed. Date-partitioned fact tables matching incremental-refresh policies. Power BI measures and relationships live in the .pbix model, so Datrise keeps the underlying tables stable and star-schema-shaped.

Ideal for Microsoft-stack self-serve reporting.

Endpoints

PostgreSQL: Self-managed PostgreSQL instances.

Microsoft Power BI: Microsoft business intelligence with datasets, reports, and semantic models.

How PostgreSQL entities map to Microsoft Power BI

PostgreSQL entityMicrosoft Power BI objectNotes
tableshp_postgres_tablesid PK · custom fields → flattened columns (nested fields expanded)
rowshp_postgres_rowsid PK · linked to hp_postgres_tables
schemashp_postgres_schemasid PK · linked to hp_postgres_tables
indexeshp_postgres_indexesid PK · linked to hp_postgres_tables

FAQ

How does Datrise handle PostgreSQL's custom fields in Microsoft Power BI?

Flexible values are stored as flattened columns (nested fields expanded), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft Power BI types.

How does the PostgreSQL to Microsoft Power BI sync stay up to date?

It runs incrementally — Datrise uses incremental-refresh windows aligned to Power BI's RangeStart/RangeEnd.

Related pipelines

Early access

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