DatriseAI-first ETL

AppsFlyer Google BigQuery

AI-first ETL from AppsFlyer into Google BigQuery. Governed entities, incremental sync, typed landing tables.

How Datrise loads AppsFlyer into Google BigQuery

Datrise syncs AppsFlyer's installs, in-app events, campaigns, and attribution touchpoints into Google BigQuery as a partitioned table per source entity. Flexible or custom fields land in JSON or nested/repeated (STRUCT) columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target, so re-runs update only what changed. Partition by ingestion or event date and cluster by entity id to keep scanned bytes low. BigQuery bills by bytes scanned, so Datrise partitions and clusters every table to keep query costs predictable.

Ideal for Google-stack analytics and ML on serverless infrastructure.

Endpoints

AppsFlyer: Mobile attribution and marketing analytics platform.

Google BigQuery: Serverless analytics warehouse on GCP.

How AppsFlyer entities map to Google BigQuery

AppsFlyer entityGoogle BigQuery objectNotes
installsappsflyer_installsid PK · custom fields → JSON or nested/repeated (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 Google BigQuery?

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

How does the AppsFlyer to Google BigQuery sync stay up to date?

It runs incrementally — Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target.

Related pipelines

Early access

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