PostgreSQL to Redash Integration
AI-first ETL from PostgreSQL into Redash. Governed entities, incremental sync, typed landing tables.
How Datrise loads PostgreSQL into Redash
Datrise syncs PostgreSQL's tables, rows, schemas, indexes, sequences, and replication slots into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.
Ideal for lightweight, query-driven dashboards.
Endpoints
PostgreSQL: Self-managed PostgreSQL instances.
Redash: Open-source SQL client for queries, visualizations, and dashboards.
How PostgreSQL entities map to Redash
| PostgreSQL entity | Redash object | Notes |
|---|---|---|
| tables | hp_postgres_tables | id PK · custom fields → flattened columns for query results |
| 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 Redash?
Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.
How does the PostgreSQL to Redash sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for PostgreSQL
Early access
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