Apify to Metabase Integration
AI-first ETL from Apify into Metabase. Governed entities, incremental sync, typed landing tables.
How Datrise loads Apify into Metabase
Datrise syncs Apify's actors, runs, datasets, key-value stores, request queues, and run logs 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
Apify: Web scraping and browser automation platform.
Metabase: Open-source analytics with questions, dashboards, and embedded insights.
How Apify entities map to Metabase
| Apify entity | Metabase object | Notes |
|---|---|---|
| actors | apify_actors | id PK · custom fields → flattened columns for the question builder |
| runs | apify_runs | id PK · linked to apify_actors |
| datasets | apify_datasets | id PK · linked to apify_actors |
| key-value stores | apify_key_value_stores | id PK · linked to apify_actors |
FAQ
How does Datrise handle Apify'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 Apify to Metabase sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for Apify
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