DatriseAI-first ETL

Appfollow to DuckDB Integration

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

How Datrise loads Appfollow into DuckDB

Datrise syncs Appfollow's reviews, ratings, app rankings, keywords, replies, and store listings into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

Appfollow: App store review and rankings monitoring.

DuckDB: In-process analytics database for fast local OLAP.

How Appfollow entities map to DuckDB

Appfollow entityDuckDB objectNotes
reviewsappfollow_reviewsid PK · custom fields → JSON or STRUCT columns
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 DuckDB?

Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.

How does the Appfollow to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

Early access

Connect Appfollow to DuckDB the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.