Segment → Google BigQuery
AI-first ETL from Segment into Google BigQuery. Governed entities, incremental sync, typed landing tables.
How Datrise loads Segment into Google BigQuery
Datrise syncs Segment's sources, destinations, track events, identify calls, and schema catalog 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
Segment: Customer data platform routing events to warehouses.
Google BigQuery: Serverless analytics warehouse on GCP.
How Segment entities map to Google BigQuery
| Segment entity | Google BigQuery object | Notes |
|---|---|---|
| sources | segment_sources | id PK · custom fields → JSON or nested/repeated (STRUCT) columns |
| destinations | segment_destinations | id PK · linked to segment_sources |
| track events | segment_track_events | TIMESTAMP events |
| identify calls | segment_identify_calls | id PK · linked to segment_sources |
FAQ
How does Datrise handle Segment'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 Segment 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
More destinations for Segment
More sources for Google BigQuery
Early access
Connect Segment to Google BigQuery the easy way
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