DatriseAI-first ETL

BambooHR Google BigQuery

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

How Datrise loads BambooHR into Google BigQuery

Datrise syncs BambooHR's employee records, org structure, lifecycle events, and workforce attributes 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

BambooHR: HRIS source for employee records and workforce analytics.

Google BigQuery: Serverless analytics warehouse on GCP.

How BambooHR entities map to Google BigQuery

BambooHR entityGoogle BigQuery objectNotes
employee recordsbamboohr_employee_recordsid PK · custom fields → JSON or nested/repeated (STRUCT) columns
org structurebamboohr_org_structureid PK · linked to bamboohr_employee_records
lifecycle eventsbamboohr_lifecycle_eventsTIMESTAMP events
workforce attributesbamboohr_workforce_attributesid PK · linked to bamboohr_employee_records

FAQ

How does Datrise handle BambooHR'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 BambooHR 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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