Bitrix24 → Google BigQuery
AI-first ETL from Bitrix24 into Google BigQuery. Governed entities, incremental sync, typed landing tables.
How Datrise loads Bitrix24 into Google BigQuery
Datrise syncs Bitrix24's leads, deals, contacts, companies, activities, and contact-center events into Google BigQuery as a partitioned table per source entity. Flexible or custom fields land in JSON or nested/repeated (STRUCT) columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.
Sync is incremental: Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target, so re-runs update only what changed. Partition by ingestion or event date and cluster by entity id to keep scanned bytes low. BigQuery bills by bytes scanned, so Datrise partitions and clusters every table to keep query costs predictable.
Ideal for Google-stack analytics and ML on serverless infrastructure.
Endpoints
Bitrix24: CRM, contact center, and task automation suite.
Google BigQuery: Serverless analytics warehouse on GCP.
How Bitrix24 entities map to Google BigQuery
| Bitrix24 entity | Google BigQuery object | Notes |
|---|---|---|
| leads | bitrix24_leads | id PK · custom fields → JSON or nested/repeated (STRUCT) columns |
| deals | bitrix24_deals | id PK · linked to bitrix24_leads |
| contacts | bitrix24_contacts | id PK · linked to bitrix24_leads |
| companies | bitrix24_companies | id PK · linked to bitrix24_leads |
FAQ
How does Datrise handle Bitrix24's custom fields in Google BigQuery?
Flexible values are stored as JSON or nested/repeated (STRUCT) columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Google BigQuery types.
How does the Bitrix24 to Google BigQuery sync stay up to date?
It runs incrementally — Datrise uses appends to a staging table, then MERGE on stable id into the partitioned target.
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Early access
Connect Bitrix24 to Google BigQuery the easy way
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