Heap to Mode Integration
AI-first ETL from Heap into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads Heap into Mode
Datrise syncs Heap's events, users, sessions, funnels, segments, and user properties 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
Heap: Autocaptured product analytics and funnels.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How Heap entities map to Mode
| Heap entity | Mode object | Notes |
|---|---|---|
| events | heap_events | temporal columns events |
| users | heap_users | id PK · linked to heap_events |
| sessions | heap_sessions | id PK · linked to heap_events |
| funnels | heap_funnels | id PK · linked to heap_events |
FAQ
How does Datrise handle Heap'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 Heap to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for Heap
Early access
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