DatriseAI-first ETL

Monday.com Google BigQuery

AI-first ETL from Monday.com into Google BigQuery. Governed entities, incremental sync, typed landing tables.

How Datrise loads Monday.com into Google BigQuery

Datrise syncs Monday.com's boards, items, groups, status timelines, automations, and owner activity 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

Monday.com: Work OS for CRM, projects, and workflows.

Google BigQuery: Serverless analytics warehouse on GCP.

How Monday.com entities map to Google BigQuery

Monday.com entityGoogle BigQuery objectNotes
boardsmonday_boardsid PK · custom fields → JSON or nested/repeated (STRUCT) columns
itemsmonday_itemsid PK · linked to monday_boards
groupsmonday_groupsid PK · linked to monday_boards
status timelinesmonday_status_timelinesTIMESTAMP events

FAQ

How does Datrise handle Monday.com'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 Monday.com 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.

Related pipelines

Early access

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