DatriseAI-first ETL

Kommo Snowflake

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

How Datrise loads Kommo into Snowflake

Datrise syncs Kommo's conversational CRM events, chats, leads, and sales automation triggers 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

Kommo: Conversational CRM for WhatsApp, chat funnels, and sales automation.

Snowflake: Cloud data warehouse with separated compute and storage.

How Kommo entities map to Snowflake

Kommo entitySnowflake objectNotes
conversational CRM eventskommo_conversational_crm_eventsTIMESTAMP_TZ events
chatskommo_chatsid PK · linked to kommo_conversational_crm_events
leadskommo_leadsid PK · linked to kommo_conversational_crm_events
sales automation triggerskommo_sales_automation_triggersid PK · linked to kommo_conversational_crm_events

FAQ

How does Datrise handle Kommo'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 Kommo 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

Early access

Connect Kommo to Snowflake the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.