DatriseAI-first ETL

PostgreSQL to Yellowfin Integration

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

How Datrise loads PostgreSQL into Yellowfin

Datrise syncs PostgreSQL's tables, rows, schemas, indexes, sequences, and replication slots into Yellowfin as warehouse tables Yellowfin builds views on. 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 connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.

Ideal for dashboards with automated data storytelling.

Endpoints

PostgreSQL: Self-managed PostgreSQL instances.

Yellowfin: BI suite with dashboards, automated insights, and data storytelling.

How PostgreSQL entities map to Yellowfin

PostgreSQL entityYellowfin objectNotes
tableshp_postgres_tablesid PK · custom fields → flattened columns
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 Yellowfin?

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 Yellowfin types.

How does the PostgreSQL to Yellowfin sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

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