DatriseAI-first ETL

Glassfrog to PostgreSQL Integration

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

How Datrise loads Glassfrog into PostgreSQL

Datrise syncs Glassfrog's circles, roles, people, accountabilities, projects, and governance records 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

Glassfrog: Holacracy roles, circles, and governance records.

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

How Glassfrog entities map to PostgreSQL

Glassfrog entityPostgreSQL objectNotes
circlesglassfrog_circlesid PK · custom fields → jsonb columns
rolesglassfrog_rolesid PK · linked to glassfrog_circles
peopleglassfrog_peopleid PK · linked to glassfrog_circles
accountabilitiesglassfrog_accountabilitiesid PK · linked to glassfrog_circles

FAQ

How does Datrise handle Glassfrog'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 Glassfrog 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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