DatriseAI-first ETL

Streak Google BigQuery

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

How Datrise loads Streak into Google BigQuery

Datrise syncs Streak's contacts, accounts, deals, activities, and lifecycle events 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

Streak: CRM for SMB teams managing pipeline, contacts, and customer activity.

Google BigQuery: Serverless analytics warehouse on GCP.

How Streak entities map to Google BigQuery

Streak entityGoogle BigQuery objectNotes
contactsstreak_contactsid PK · custom fields → JSON or nested/repeated (STRUCT) columns
accountsstreak_accountsid PK · linked to streak_contacts
dealsstreak_dealsid PK · linked to streak_contacts
activitiesstreak_activitiesTIMESTAMP events

FAQ

How does Datrise handle Streak'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 Streak 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 Streak 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.