DatriseAI-first ETL

CommCare to Snowflake Integration

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

How Datrise loads CommCare into Snowflake

Datrise syncs CommCare's cases, forms, form submissions, users, locations, and case properties 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

CommCare: Mobile data collection for field programs.

Snowflake: Cloud data warehouse with separated compute and storage.

How CommCare entities map to Snowflake

CommCare entitySnowflake objectNotes
casescommcare_casesid PK · custom fields → VARIANT columns
formscommcare_formsid PK · linked to commcare_cases
form submissionscommcare_form_submissionsid PK · linked to commcare_cases
userscommcare_usersid PK · linked to commcare_cases

FAQ

How does Datrise handle CommCare'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 CommCare 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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