DatriseAI-first ETL

Klaviyo Google BigQuery

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

How Datrise loads Klaviyo into Google BigQuery

Datrise syncs Klaviyo's profiles, segments, flows, campaigns, and attributed revenue 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

Klaviyo: E-commerce marketing automation with email and SMS.

Google BigQuery: Serverless analytics warehouse on GCP.

How Klaviyo entities map to Google BigQuery

Klaviyo entityGoogle BigQuery objectNotes
profilesklaviyo_profilesid PK · custom fields → JSON or nested/repeated (STRUCT) columns
segmentsklaviyo_segmentsid PK · linked to klaviyo_profiles
flowsklaviyo_flowsid PK · linked to klaviyo_profiles
campaignsklaviyo_campaignsid PK · linked to klaviyo_profiles

FAQ

How does Datrise handle Klaviyo'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 Klaviyo 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 Klaviyo 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.