1С:CRM → DuckDB
AI-first ETL from 1С:CRM into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads 1С:CRM into DuckDB
Datrise syncs 1С:CRM's contacts, accounts, deals, activities, and lifecycle events into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.
Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.
Ideal for local and notebook analytics without standing up a server.
Endpoints
1С:CRM: CRM with strong adoption in CIS markets for sales and operations.
DuckDB: In-process analytics database for fast local OLAP.
How 1С:CRM entities map to DuckDB
| 1С:CRM entity | DuckDB object | Notes |
|---|---|---|
| contacts | 1c_crm_contacts | id PK · custom fields → JSON or STRUCT columns |
| accounts | 1c_crm_accounts | id PK · linked to 1c_crm_contacts |
| deals | 1c_crm_deals | id PK · linked to 1c_crm_contacts |
| activities | 1c_crm_activities | TIMESTAMP WITH TIME ZONE events |
FAQ
How does Datrise handle 1С:CRM's custom fields in DuckDB?
Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.
How does the 1С:CRM to DuckDB sync stay up to date?
It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.
Related pipelines
More destinations for 1С:CRM
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