DatriseAI-first ETL

Maximizer CRM to Google BigQuery Integration

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

How Datrise loads Maximizer CRM into Google BigQuery

Datrise syncs Maximizer CRM's address book entries, opportunities, customer service cases, interactions, notes, and campaigns 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

Maximizer CRM: Long-standing CRM for address book and case tracking.

Google BigQuery: Serverless analytics warehouse on GCP.

How Maximizer CRM entities map to Google BigQuery

Maximizer CRM entityGoogle BigQuery objectNotes
address book entriesmaximizer_address_book_entriesid PK · custom fields → JSON or nested/repeated (STRUCT) columns
opportunitiesmaximizer_opportunitiesid PK · linked to maximizer_address_book_entries
customer service casesmaximizer_customer_service_casesid PK · linked to maximizer_address_book_entries
interactionsmaximizer_interactionsid PK · linked to maximizer_address_book_entries

FAQ

How does Datrise handle Maximizer CRM'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 Maximizer CRM 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 Maximizer CRM 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.