Auth0 → Mode
AI-first ETL from Auth0 into Mode. Governed entities, incremental sync, typed landing tables.
How Datrise loads Auth0 into Mode
Datrise syncs Auth0's authentication logs, sign-ins, user identity changes, and security events into Mode as warehouse tables Mode queries with SQL. Flexible or custom fields land in flattened columns for SQL and notebooks, and timestamps such as created, updated, and status changes are typed as temporal columns.
Sync is incremental: Datrise uses incremental refresh of the queried tables, so re-runs update only what changed. Date-partitioned facts for report queries. Mode runs analyst-written SQL, so Datrise lands stable, documented tables that won't break saved reports.
Ideal for SQL-first analysis with Python and R notebooks.
Endpoints
Auth0: Identity source for authentication and sign-in telemetry.
Mode: Collaborative analytics workspace for SQL, Python, and shared reports.
How Auth0 entities map to Mode
| Auth0 entity | Mode object | Notes |
|---|---|---|
| authentication logs | auth0_authentication_logs | id PK · custom fields → flattened columns for SQL and notebooks |
| sign-ins | auth0_sign_ins | id PK · linked to auth0_authentication_logs |
| user identity changes | auth0_user_identity_changes | temporal columns events |
| security events | auth0_security_events | temporal columns events |
FAQ
How does Datrise handle Auth0's custom fields in Mode?
Flexible values are stored as flattened columns for SQL and notebooks, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Mode types.
How does the Auth0 to Mode sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the queried tables.
Related pipelines
More destinations for Auth0
Early access
Connect Auth0 to Mode the easy way
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