DatriseAI-first ETL

SuiteCRM Google BigQuery

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

How Datrise loads SuiteCRM into Google BigQuery

Datrise syncs SuiteCRM's open-source CRM entities, custom modules, and configurable workflows 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

SuiteCRM: Open-source CRM for customizable sales and customer operations.

Google BigQuery: Serverless analytics warehouse on GCP.

How SuiteCRM entities map to Google BigQuery

SuiteCRM entityGoogle BigQuery objectNotes
open-source CRM entitiessuitecrm_open_source_crm_entitiesid PK · custom fields → JSON or nested/repeated (STRUCT) columns
custom modulessuitecrm_custom_modulesid PK · linked to suitecrm_open_source_crm_entities
configurable workflowssuitecrm_configurable_workflowsid PK · linked to suitecrm_open_source_crm_entities

FAQ

How does Datrise handle SuiteCRM'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 SuiteCRM 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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