DatriseAI-first ETL

Appfollow to Amazon Redshift Integration

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

How Datrise loads Appfollow into Amazon Redshift

Datrise syncs Appfollow's reviews, ratings, app rankings, keywords, replies, and store listings into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.

Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.

Ideal for AWS-native warehouses already using the Redshift ecosystem.

Endpoints

Appfollow: App store review and rankings monitoring.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How Appfollow entities map to Amazon Redshift

Appfollow entityAmazon Redshift objectNotes
reviewsappfollow_reviewsid PK · custom fields → SUPER 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 Amazon Redshift?

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

How does the Appfollow to Amazon Redshift sync stay up to date?

It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.

Related pipelines

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