AppsFlyer → Mode
AI-first ETL from AppsFlyer into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads AppsFlyer into Mode
Datrise syncs AppsFlyer's installs, in-app events, campaigns, and attribution touchpoints into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
AppsFlyer: Mobile attribution and marketing analytics platform.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How AppsFlyer entities map to Mode
| AppsFlyer entity | Mode object | Notes |
|---|---|---|
| installs | appsflyer_installs | id PK · custom fields → flattened columns for SQL and notebooks |
| in-app events | appsflyer_in_app_events | temporal columns events |
| campaigns | appsflyer_campaigns | id PK · linked to appsflyer_installs |
| attribution touchpoints | appsflyer_attribution_touchpoints | id PK · linked to appsflyer_installs |
FAQ
How does Datrise handle AppsFlyer's custom fields in Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the AppsFlyer to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for AppsFlyer
Early access
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