DatriseAI-first ETL

Appfollow to CSV Files Integration

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

How Datrise loads Appfollow into CSV Files

Datrise syncs Appfollow's reviews, ratings, app rankings, keywords, replies, and store listings 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

Appfollow: App store review and rankings monitoring.

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

How Appfollow entities map to CSV Files

Appfollow entityCSV Files objectNotes
reviewsappfollow_reviewsid PK · custom fields → JSON-encoded strings for nested fields
ratingsappfollow_ratingsid PK · linked to appfollow_reviews
app rankingsappfollow_app_rankingsid PK · linked to appfollow_reviews
keywordsappfollow_keywordsid PK · linked to appfollow_reviews

FAQ

How does Datrise handle Appfollow'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 Appfollow 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

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