DatriseAI-first ETL

Twenty CRM to Snowflake Integration

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

How Datrise loads Twenty CRM into Snowflake

Datrise syncs Twenty CRM's people, companies, opportunities, notes, tasks, and custom objects 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

Twenty CRM: Open-source CRM with a customizable object model.

Snowflake: Cloud data warehouse with separated compute and storage.

How Twenty CRM entities map to Snowflake

Twenty CRM entitySnowflake objectNotes
peopletwenty_peopleid PK · custom fields → VARIANT columns
companiestwenty_companiesid PK · linked to twenty_people
opportunitiestwenty_opportunitiesid PK · linked to twenty_people
notestwenty_notesid PK · linked to twenty_people

FAQ

How does Datrise handle Twenty CRM'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 Twenty CRM 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.

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