DatriseAI-first ETL

Google Cloud Storage to Holistics Integration

AI-first ETL from Google Cloud Storage into Holistics. Governed entities, incremental sync, typed landing tables.

How Datrise loads Google Cloud Storage into Holistics

Datrise syncs Google Cloud Storage's buckets, objects, prefixes, object metadata, generations, and storage classes 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 Storage: Object storage for files and data lake exports on GCP.

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

How Google Cloud Storage entities map to Holistics

Google Cloud Storage entityHolistics objectNotes
bucketsgoogle_cloud_storage_f_bucketsid PK · custom fields → flattened columns for the modeling layer
objectsgoogle_cloud_storage_f_objectsid PK · linked to google_cloud_storage_f_buckets
prefixesgoogle_cloud_storage_f_prefixesid PK · linked to google_cloud_storage_f_buckets
object metadatagoogle_cloud_storage_f_object_metadataid PK · linked to google_cloud_storage_f_buckets

FAQ

How does Datrise handle Google Cloud Storage'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 Storage 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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