DatriseAI-first ETL

Kommo Azure Data Lake Storage

AI-first ETL from Kommo into Azure Data Lake Storage. Governed entities, incremental sync, typed landing tables.

How Datrise loads Kommo into Azure Data Lake Storage

Datrise syncs Kommo's conversational CRM events, chats, leads, and sales automation triggers into Azure Data Lake Storage as partitioned Parquet in ADLS Gen2 per source entity. Flexible or custom fields land in nested struct/map fields in Parquet, and timestamps such as created, updated, and status changes are typed as ISO-8601 timestamp columns.

Sync is incremental: Datrise uses writes new date partitions to the container and compacts on a schedule, so re-runs update only what changed. Hive-style partitioning by load date, readable by Synapse and Databricks. ADLS hierarchical namespace makes folder layout matter, so Datrise keeps a predictable entity/date path your Azure engines mount directly.

Ideal for Azure lakehouse storage shared across Synapse and Databricks.

Endpoints

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

Azure Data Lake Storage: ADLS Gen2 object storage for analytics workloads.

How Kommo entities map to Azure Data Lake Storage

Kommo entityAzure Data Lake Storage objectNotes
conversational CRM eventskommo_conversational_crm_eventsISO-8601 timestamp 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 Azure Data Lake Storage?

Flexible values are stored as nested struct/map fields in Parquet, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Azure Data Lake Storage types.

How does the Kommo to Azure Data Lake Storage sync stay up to date?

It runs incrementally — Datrise uses writes new date partitions to the container and compacts on a schedule.

Related pipelines

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