DatriseAI-first ETL

Close Com Google BigQuery

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

How Datrise loads Close Com into Google BigQuery

Datrise syncs Close Com's records, events, and configuration objects 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

Close Com: SaaS or API data source for analytics and warehouse sync.

Google BigQuery: Serverless analytics warehouse on GCP.

How Close Com entities map to Google BigQuery

Close Com entityGoogle BigQuery objectNotes
recordsclose_com_recordsid PK · custom fields → JSON or nested/repeated (STRUCT) columns
eventsclose_com_eventsTIMESTAMP events
configuration objectsclose_com_configuration_objectsid PK · linked to close_com_records

FAQ

How does Datrise handle Close 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 Close 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

Connect Close Com to Google BigQuery the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.