PostgreSQL to Amazon QuickSight Integration

How Datrise loads PostgreSQL into Amazon QuickSight

Datrise syncs PostgreSQL's tables, rows, schemas, indexes, sequences, and replication slots into Amazon QuickSight as warehouse tables or a SPICE-loaded dataset. Flexible or custom fields land in flattened columns for analyses, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental refresh of the tables behind SPICE or direct query, so re-runs update only what changed. Date-partitioned facts to bound SPICE refresh. QuickSight SPICE is an in-memory copy, so Datrise keeps the backing tables incremental so refreshes stay cheap.

Ideal for AWS-native dashboards with pay-per-session pricing.

Endpoints

PostgreSQL: Self-managed PostgreSQL instances.

Amazon QuickSight: AWS serverless BI with SPICE and embedded analytics.

How PostgreSQL entities map to Amazon QuickSight

PostgreSQL entity	Amazon QuickSight object	Notes
tables	`hp_postgres_tables`	id PK · custom fields → flattened columns for analyses
rows	`hp_postgres_rows`	id PK · linked to hp_postgres_tables
schemas	`hp_postgres_schemas`	id PK · linked to hp_postgres_tables
indexes	`hp_postgres_indexes`	id PK · linked to hp_postgres_tables

FAQ

How does Datrise handle PostgreSQL's custom fields in Amazon QuickSight?

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

How does the PostgreSQL to Amazon QuickSight sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the tables behind SPICE or direct query.

Related pipelines

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