DatriseAI-first ETL

Snowflake to PostgreSQL Integration

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

How Datrise loads Snowflake into PostgreSQL

Datrise syncs Snowflake's databases, schemas, tables, views, query history, and warehouses into PostgreSQL as a typed table per source entity. Flexible or custom fields land in jsonb columns, and timestamps such as created, updated, and status changes are typed as timestamptz.

Sync is incremental: Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE, so re-runs update only what changed. Optional declarative range partitioning by load date for high-volume tables. PostgreSQL folds unquoted identifiers to lowercase, so Datrise normalizes mixed-case source fields to snake_case.

Ideal for operational analytics and application backends that need fresh, queryable copies of your data.

Endpoints

Snowflake: Cloud data platform with separated storage and compute.

PostgreSQL: Open-source relational database with strong SQL and extensions.

How Snowflake entities map to PostgreSQL

Snowflake entityPostgreSQL objectNotes
databasessnowflake_databasesid PK · custom fields → jsonb columns
schemassnowflake_schemasid PK · linked to snowflake_databases
tablessnowflake_tablesid PK · linked to snowflake_databases
viewssnowflake_viewsid PK · linked to snowflake_databases

FAQ

How does Datrise handle Snowflake's custom fields in PostgreSQL?

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

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

It runs incrementally — Datrise uses a watermark on each entity's updated-at, applied with INSERT … ON CONFLICT DO UPDATE.

Related pipelines

Early access

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