DatriseAI-first ETL

PostgreSQL to Databricks SQL Warehouse Integration

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

How Datrise loads PostgreSQL into Databricks SQL Warehouse

Datrise syncs PostgreSQL's tables, rows, schemas, indexes, sequences, and replication slots into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

PostgreSQL: Self-managed PostgreSQL instances.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How PostgreSQL entities map to Databricks SQL Warehouse

PostgreSQL entityDatabricks SQL Warehouse objectNotes
tableshp_postgres_tablesid PK · custom fields → VARIANT or STRUCT 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 Databricks SQL Warehouse?

Flexible values are stored as VARIANT or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Databricks SQL Warehouse types.

How does the PostgreSQL to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

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