DatriseAI-first ETL

Auth0 Microsoft SQL Server

AI-first ETL from Auth0 into Microsoft SQL Server. Governed entities, incremental sync, typed landing tables.

How Datrise loads Auth0 into Microsoft SQL Server

Datrise syncs Auth0's authentication logs, sign-ins, user identity changes, and security events 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

Auth0: Identity source for authentication and sign-in telemetry.

Microsoft SQL Server: Microsoft relational DB with enterprise features.

How Auth0 entities map to Microsoft SQL Server

Auth0 entityMicrosoft SQL Server objectNotes
authentication logsauth0_authentication_logsid PK · custom fields → NVARCHAR(MAX) JSON columns
sign-insauth0_sign_insid PK · linked to auth0_authentication_logs
user identity changesauth0_user_identity_changesdatetime2 events
security eventsauth0_security_eventsdatetime2 events

FAQ

How does Datrise handle Auth0'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 Auth0 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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