DatriseAI-first ETL

CockroachDB to Google BigQuery Integration

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

How Datrise loads CockroachDB into Google BigQuery

Datrise syncs CockroachDB's tables, rows, schemas, secondary indexes, ranges, and change feeds 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

CockroachDB: Distributed SQL with survivable multi-region consistency.

Google BigQuery: Serverless analytics warehouse on GCP.

How CockroachDB entities map to Google BigQuery

CockroachDB entityGoogle BigQuery objectNotes
tablescockroachdb_tablesid PK · custom fields → JSON or nested/repeated (STRUCT) columns
rowscockroachdb_rowsid PK · linked to cockroachdb_tables
schemascockroachdb_schemasid PK · linked to cockroachdb_tables
secondary indexescockroachdb_secondary_indexesid PK · linked to cockroachdb_tables

FAQ

How does Datrise handle CockroachDB'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 CockroachDB 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

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