DatriseAI-first ETL

Bitrix24 DuckDB

AI-first ETL from Bitrix24 into DuckDB. Governed entities, incremental sync, typed landing tables.

How Datrise loads Bitrix24 into DuckDB

Datrise syncs Bitrix24's leads, deals, contacts, companies, activities, and contact-center 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

Bitrix24: CRM, contact center, and task automation suite.

DuckDB: In-process analytics database for fast local OLAP.

How Bitrix24 entities map to DuckDB

Bitrix24 entityDuckDB objectNotes
leadsbitrix24_leadsid PK · custom fields → JSON or STRUCT columns
dealsbitrix24_dealsid PK · linked to bitrix24_leads
contactsbitrix24_contactsid PK · linked to bitrix24_leads
companiesbitrix24_companiesid PK · linked to bitrix24_leads

FAQ

How does Datrise handle Bitrix24'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 Bitrix24 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

Early access

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