AppsFlyer → Amazon S3 Data Lake
AI-first ETL from AppsFlyer into Amazon S3 Data Lake. Governed entities, incremental sync, typed landing tables.
How Datrise loads AppsFlyer into Amazon S3 Data Lake
Datrise syncs AppsFlyer's installs, in-app events, campaigns, and attribution touchpoints into Amazon S3 Data Lake as columnar Parquet objects partitioned per source entity. Flexible or custom fields land in nested struct/map fields in Parquet, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.
Sync is incremental: Datrise uses writes new date partitions and compacts small files on a schedule, so re-runs update only what changed. Hive-style path partitioning (entity/date) for engine-agnostic reads. A lake has no schema enforcement, so Datrise writes a schema manifest alongside the data to keep downstream engines consistent.
Ideal for an open, engine-neutral storage layer for Spark, Athena, Trino, or DuckDB.
Endpoints
AppsFlyer: Mobile attribution and marketing analytics platform.
Amazon S3 Data Lake: Object storage landing zone for parquet and snapshots.
How AppsFlyer entities map to Amazon S3 Data Lake
| AppsFlyer entity | Amazon S3 Data Lake object | Notes |
|---|---|---|
| installs | appsflyer_installs | id PK · custom fields → nested struct/map fields in Parquet |
| in-app events | appsflyer_in_app_events | ISO-8601 timestamp 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 Amazon S3 Data Lake?
Flexible values are stored as nested struct/map fields in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Amazon S3 Data Lake types.
How does the AppsFlyer to Amazon S3 Data Lake sync stay up to date?
It runs incrementally — Datrise uses writes new date partitions and compacts small files on a schedule.
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Early access
Connect AppsFlyer to Amazon S3 Data Lake 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.