DatriseAI-first ETL

Kommo Redash

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

How Datrise loads Kommo into Redash

Datrise syncs Kommo's conversational CRM events, chats, leads, and sales automation triggers into Redash as SQL tables Redash queries and visualizes. Flexible or custom fields land in flattened columns for query results, and timestamps such as created, updated, and status changes are typed as temporal columns.

Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts for scheduled queries. Redash caches query results on a schedule, so Datrise keeps tables incrementally fresh so cached dashboards reflect reality.

Ideal for lightweight, query-driven dashboards.

Endpoints

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

Redash: Open-source SQL client for queries, visualizations, and dashboards.

How Kommo entities map to Redash

Kommo entityRedash objectNotes
conversational CRM eventskommo_conversational_crm_eventstemporal columns 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 Redash?

Flexible values are stored as flattened columns for query results, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Redash types.

How does the Kommo to Redash sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the connected tables.

Related pipelines

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