Google Cloud SQL to Holistics Integration

How Datrise loads Google Cloud SQL into Holistics

Datrise syncs Google Cloud SQL's tables, rows, schemas, indexes, read replicas, and binlog changes into Holistics as warehouse tables modeled in Holistics. Flexible or custom fields land in flattened columns for the modeling layer, and timestamps such as created, updated, and status changes are typed as date/time dimensions.

Sync is incremental: Datrise uses incremental refresh of the modeled tables, so re-runs update only what changed. Date-partitioned facts for fast aggregates. Holistics models data as code on top of SQL, so Datrise lands stable column names to keep your models from drifting.

Ideal for as-code BI modeling on a warehouse.

Endpoints

Google Cloud SQL: Managed MySQL, PostgreSQL, and SQL Server instances on GCP.

Holistics: Self-service BI with modeling layers and scheduled report delivery.

How Google Cloud SQL entities map to Holistics

Google Cloud SQL entity	Holistics object	Notes
tables	`google_cloud_sql_tables`	id PK · custom fields → flattened columns for the modeling layer
rows	`google_cloud_sql_rows`	id PK · linked to google_cloud_sql_tables
schemas	`google_cloud_sql_schemas`	id PK · linked to google_cloud_sql_tables
indexes	`google_cloud_sql_indexes`	id PK · linked to google_cloud_sql_tables

FAQ

How does Datrise handle Google Cloud SQL's custom fields in Holistics?

Flexible values are stored as flattened columns for the modeling layer, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Holistics types.

How does the Google Cloud SQL to Holistics sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the modeled tables.

Related pipelines

Early access

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