Kommo → DuckDB
AI-first ETL from Kommo into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Kommo into DuckDB
Datrise syncs Kommo's conversational CRM events, chats, leads, and sales automation triggers 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
Kommo: Conversational CRM for WhatsApp, chat funnels, and sales automation.
DuckDB: In-process analytics database for fast local OLAP.
How Kommo entities map to DuckDB
| Kommo entity | DuckDB object | Notes |
|---|---|---|
| conversational CRM events | kommo_conversational_crm_events | TIMESTAMP WITH TIME ZONE events |
| chats | kommo_chats | id PK · linked to kommo_conversational_crm_events |
| leads | kommo_leads | id PK · linked to kommo_conversational_crm_events |
| sales automation triggers | kommo_sales_automation_triggers | id PK · linked to kommo_conversational_crm_events |
FAQ
How does Datrise handle Kommo'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 Kommo to DuckDB sync stay up to date?
It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.
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