DatriseAI-first ETL

Ip2whois Microsoft SQL Server

AI-first ETL from Ip2whois into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.

How Datrise loads Ip2whois into Microsoft SQL Server

Datrise syncs Ip2whois's records, events, and configuration objects into Microsoft SQL Server as a typed table per source entity. Flexible or custom fields land in NVARCHAR(MAX) JSON columns, and timestamps such as created, updated, and status changes are typed as datetime2.

Sync is incremental: Datrise uses a watermark on updated-at, applied with a MERGE statement, so re-runs update only what changed. Optional partitioned tables on a date partition function. SQL Server defaults to a case-insensitive collation, so Datrise preserves original casing in a metadata column to avoid silent key collisions.

Ideal for Microsoft-stack analytics and Power BI Import models.

Endpoints

Ip2whois: SaaS or API data source for analytics and warehouse sync.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Ip2whois entities map to Microsoft SQL Server

Ip2whois entityMicrosoft SQL Server objectNotes
recordsip2whois_recordsid PK · custom fields → NVARCHAR(MAX) JSON columns
eventsip2whois_eventsdatetime2 events
configuration objectsip2whois_configuration_objectsid PK · linked to ip2whois_records

FAQ

How does Datrise handle Ip2whois's custom fields in Microsoft SQL Server?

Flexible values are stored as NVARCHAR(MAX) JSON columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Microsoft SQL Server types.

How does the Ip2whois to Microsoft SQL Server sync stay up to date?

It runs incrementally — Datrise uses a watermark on updated-at, applied with a MERGE statement.

Related pipelines

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