DatriseAI-first ETL

AppsFlyer Databricks SQL Warehouse

AI-first ETL from AppsFlyer into Databricks SQL Warehouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads AppsFlyer into Databricks SQL Warehouse

Datrise syncs AppsFlyer's installs, in-app events, campaigns, and attribution touchpoints into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

AppsFlyer: Mobile attribution and marketing analytics platform.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How AppsFlyer entities map to Databricks SQL Warehouse

AppsFlyer entityDatabricks SQL Warehouse objectNotes
installsappsflyer_installsid PK · custom fields → VARIANT or STRUCT columns
in-app eventsappsflyer_in_app_eventsTIMESTAMP events
campaignsappsflyer_campaignsid PK · linked to appsflyer_installs
attribution touchpointsappsflyer_attribution_touchpointsid PK · linked to appsflyer_installs

FAQ

How does Datrise handle AppsFlyer's custom fields in Databricks SQL Warehouse?

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

How does the AppsFlyer to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

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