DatriseAI-first ETL

PostgreSQL to Tableau Integration

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

How Datrise loads PostgreSQL into Tableau

Datrise syncs PostgreSQL's tables, rows, schemas, indexes, sequences, and replication slots into Tableau as warehouse tables or a refreshed .hyper extract. Flexible or custom fields land in flattened columns for Tableau fields, and timestamps such as created, updated, and status changes are typed as date/datetime fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind a live connection or extract, so re-runs update only what changed. Date-partitioned facts to keep extract refresh quick. Tableau .hyper extracts snapshot data, so Datrise keeps the source tables incremental and lets you choose live vs extract.

Ideal for visual analytics and dashboards in Tableau.

Endpoints

PostgreSQL: Self-managed PostgreSQL instances.

Tableau: Salesforce analytics platform for interactive dashboards and visual exploration.

How PostgreSQL entities map to Tableau

PostgreSQL entityTableau objectNotes
tableshp_postgres_tablesid PK · custom fields → flattened columns for Tableau fields
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 Tableau?

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

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

It runs incrementally — Datrise uses incremental refresh of the tables behind a live connection or extract.

Related pipelines

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