DatriseAI-first ETL

Glassfrog Metabase

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

How Datrise loads Glassfrog into Metabase

Datrise syncs Glassfrog's records, events, and configuration objects into Metabase as clean SQL tables Metabase auto-discovers. Flexible or custom fields land in flattened columns for the question builder, and timestamps such as created, updated, and status changes are typed as temporal columns for trends.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for large questions. Metabase auto-scans schemas, so Datrise uses readable table and column names so the no-code UI stays self-explanatory.

Ideal for self-serve questions and dashboards for whole teams.

Endpoints

Glassfrog: SaaS or API data source for analytics and warehouse sync.

Metabase: Open-source analytics with questions, dashboards, and embedded insights.

How Glassfrog entities map to Metabase

Glassfrog entityMetabase objectNotes
recordsglassfrog_recordsid PK · custom fields → flattened columns for the question builder
eventsglassfrog_eventstemporal columns for trends events
configuration objectsglassfrog_configuration_objectsid PK · linked to glassfrog_records

FAQ

How does Datrise handle Glassfrog's custom fields in Metabase?

Flexible values are stored as flattened columns for the question builder, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Metabase types.

How does the Glassfrog to Metabase sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

Early access

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