Auth0 → DuckDB
AI-first ETL from Auth0 into DuckDB. Governed entities, incremental sync, typed landing tables.
How Datrise loads Auth0 into DuckDB
Datrise syncs Auth0's authentication logs, sign-ins, user identity changes, and security events into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.
Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.
Ideal for local and notebook analytics without standing up a server.
Endpoints
Auth0: Identity source for authentication and sign-in telemetry.
DuckDB: In-process analytics database for fast local OLAP.
How Auth0 entities map to DuckDB
| Auth0 entity | DuckDB object | Notes |
|---|---|---|
| authentication logs | auth0_authentication_logs | id PK · custom fields → JSON or STRUCT columns |
| sign-ins | auth0_sign_ins | id PK · linked to auth0_authentication_logs |
| user identity changes | auth0_user_identity_changes | TIMESTAMP WITH TIME ZONE events |
| security events | auth0_security_events | TIMESTAMP WITH TIME ZONE events |
FAQ
How does Datrise handle Auth0's custom fields in DuckDB?
Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.
How does the Auth0 to DuckDB sync stay up to date?
It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.
Related pipelines
More destinations for Auth0
Early access
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