Amplitude → Mode
AI-first ETL from Amplitude into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads Amplitude into Mode
Datrise syncs Amplitude's product events, user properties, funnels, cohorts, and retention curves 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
Amplitude: Product analytics source for events, funnels, and cohorts.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How Amplitude entities map to Mode
| Amplitude entity | Mode object | Notes |
|---|---|---|
| product events | amplitude_product_events | temporal columns events |
| user properties | amplitude_user_properties | id PK · linked to amplitude_product_events |
| funnels | amplitude_funnels | id PK · linked to amplitude_product_events |
| cohorts | amplitude_cohorts | id PK · linked to amplitude_product_events |
FAQ
How does Datrise handle Amplitude'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 Amplitude to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for Amplitude
Early access
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