DatriseAI-first ETL

Chargebee Google BigQuery

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

How Datrise loads Chargebee into Google BigQuery

Datrise syncs Chargebee's subscriptions, invoices, customers, plans, and revenue 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

Chargebee: Subscription billing and revenue operations platform.

Google BigQuery: Serverless analytics warehouse on GCP.

How Chargebee entities map to Google BigQuery

Chargebee entityGoogle BigQuery objectNotes
subscriptionschargebee_subscriptionsid PK · custom fields → JSON or nested/repeated (STRUCT) columns
invoiceschargebee_invoicesid PK · linked to chargebee_subscriptions
customerschargebee_customersid PK · linked to chargebee_subscriptions
planschargebee_plansid PK · linked to chargebee_subscriptions

FAQ

How does Datrise handle Chargebee'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 Chargebee 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 Chargebee to Google BigQuery the easy way

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