1С:CRM to Snowflake Integration
AI-first ETL from 1С:CRM into Snowflake. Governed entities, incremental sync, typed landing tables.
How Datrise loads 1С:CRM into Snowflake
Datrise syncs 1С:CRM's counterparties, deals, interactions, orders, tasks, and business processes 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
1С:CRM: CRM built on the 1C platform for sales and back-office.
Snowflake: Cloud data warehouse with separated compute and storage.
How 1С:CRM entities map to Snowflake
| 1С:CRM entity | Snowflake object | Notes |
|---|---|---|
| counterparties | 1c_crm_counterparties | id PK · custom fields → VARIANT columns |
| deals | 1c_crm_deals | id PK · linked to 1c_crm_counterparties |
| interactions | 1c_crm_interactions | id PK · linked to 1c_crm_counterparties |
| orders | 1c_crm_orders | id PK · linked to 1c_crm_counterparties |
FAQ
How does Datrise handle 1С: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 1С: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.
Related pipelines
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