Ip2whois → Holistics
AI-first ETL from Ip2whois into Holistics. Governed entities, incremental sync, typed landing tables.
How Datrise loads Ip2whois into Holistics
Datrise syncs Ip2whois's records, events, and configuration objects 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
Ip2whois: SaaS or API data source for analytics and warehouse sync.
Holistics: Self-service BI with modeling layers and scheduled report delivery.
How Ip2whois entities map to Holistics
| Ip2whois entity | Holistics object | Notes |
|---|---|---|
| records | ip2whois_records | id PK · custom fields → flattened columns for the modeling layer |
| events | ip2whois_events | date/time dimensions events |
| configuration objects | ip2whois_configuration_objects | id PK · linked to ip2whois_records |
FAQ
How does Datrise handle Ip2whois'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 Ip2whois to Holistics sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the modeled tables.
Related pipelines
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