DatriseAI-first ETL

Glassfrog to CSV Files Integration

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

How Datrise loads Glassfrog into CSV Files

Datrise syncs Glassfrog's circles, roles, people, accountabilities, projects, and governance records into CSV Files as one CSV per source entity. Flexible or custom fields land in JSON-encoded strings for nested fields, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes a fresh, fully-typed CSV per entity each run, so re-runs update only what changed. Optional date-suffixed files for change tracking. CSV has no types, so Datrise emits a companion schema and quotes/escapes consistently so downstream loaders don't misparse commas and newlines.

Ideal for portable hand-off into any tool that ingests delimited files.

Endpoints

Glassfrog: Holacracy roles, circles, and governance records.

CSV Files: Flat-file destination for exports and lightweight data sharing.

How Glassfrog entities map to CSV Files

Glassfrog entityCSV Files objectNotes
circlesglassfrog_circlesid PK · custom fields → JSON-encoded strings for nested fields
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 CSV Files?

Flexible values are stored as JSON-encoded strings for nested fields, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native CSV Files types.

How does the Glassfrog to CSV Files sync stay up to date?

It runs incrementally — Datrise uses writes a fresh, fully-typed CSV per entity each run.

Related pipelines

Early access

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