DatriseAI-first ETL

Wise Agent to Google BigQuery Integration

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

How Datrise loads Wise Agent into Google BigQuery

Datrise syncs Wise Agent's contacts, transactions, listings, commissions, referrals, and checklists 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

Wise Agent: Real estate CRM for transactions, commissions, and referrals.

Google BigQuery: Serverless analytics warehouse on GCP.

How Wise Agent entities map to Google BigQuery

Wise Agent entityGoogle BigQuery objectNotes
contactswise_agent_contactsid PK · custom fields → JSON or nested/repeated (STRUCT) columns
transactionswise_agent_transactionsid PK · linked to wise_agent_contacts
listingswise_agent_listingsid PK · linked to wise_agent_contacts
commissionswise_agent_commissionsid PK · linked to wise_agent_contacts

FAQ

How does Datrise handle Wise Agent'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 Wise Agent 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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