DatriseAI-first ETL

Amplitude Azure Data Lake Storage

AI-first ETL from Amplitude into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.

How Datrise loads Amplitude into Azure Data Lake Storage

Datrise syncs Amplitude's product events, user properties, funnels, cohorts, and retention curves into Azure Data Lake Storage as partitioned Parquet in ADLS Gen2 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 to the container and compacts on a schedule, so re-runs update only what changed. Hive-style partitioning by load date, readable by Synapse and Databricks. ADLS hierarchical namespace makes folder layout matter, so Datrise keeps a predictable entity/date path your Azure engines mount directly.

Ideal for Azure lakehouse storage shared across Synapse and Databricks.

Endpoints

Amplitude: Product analytics source for events, funnels, and cohorts.

Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.

How Amplitude entities map to Azure Data Lake Storage

Amplitude entityAzure Data Lake Storage objectNotes
product eventsamplitude_product_eventsISO-8601 timestamp columns events
user propertiesamplitude_user_propertiesid PK · linked to amplitude_product_events
funnelsamplitude_funnelsid PK · linked to amplitude_product_events
cohortsamplitude_cohortsid PK · linked to amplitude_product_events

FAQ

How does Datrise handle Amplitude's custom fields in Azure Data Lake Storage?

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 Azure Data Lake Storage types.

How does the Amplitude to Azure Data Lake Storage sync stay up to date?

It runs incrementally — Datrise uses writes new date partitions to the container and compacts on a schedule.

Related pipelines

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