Looker to PostgreSQL Integration

How Datrise loads Looker into PostgreSQL

Datrise syncs Looker's looks, dashboards, explores, queries, users, and scheduled plans 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

Looker: BI platform with a modeled semantic layer.

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

How Looker entities map to PostgreSQL

Looker entity	PostgreSQL object	Notes
looks	`looker_looks`	id PK · custom fields → jsonb columns
dashboards	`looker_dashboards`	id PK · linked to looker_looks
explores	`looker_explores`	id PK · linked to looker_looks
queries	`looker_queries`	id PK · linked to looker_looks

FAQ

How does Datrise handle Looker'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 Looker 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

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