DatriseAI-first ETL

Amplitude Snowflake

AI-first ETL from Amplitude into Snowflake. Governed entities, incremental sync, typed landing tables.

How Datrise loads Amplitude into Snowflake

Datrise syncs Amplitude's product events, user properties, funnels, cohorts, and retention curves into Snowflake as a typed table per source entity. Flexible or custom fields land in VARIANT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP_TZ.

Sync is incremental: Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size, so re-runs update only what changed. Automatic micro-partitioning, with optional clustering keys on high-cardinality ids. Snowflake upper-cases unquoted identifiers, so Datrise standardizes on lower-case quoted names to keep column references stable.

Ideal for central analytics warehouses feeding BI and AI workloads.

Endpoints

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

Snowflake: Cloud data warehouse with separated compute and storage.

How Amplitude entities map to Snowflake

Amplitude entitySnowflake objectNotes
product eventsamplitude_product_eventsTIMESTAMP_TZ 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 Snowflake?

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

How does the Amplitude to Snowflake sync stay up to date?

It runs incrementally — Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size.

Related pipelines

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