Auth0 → ClickHouse
AI-first ETL from Auth0 into ClickHouse. Governed entities, incremental sync, typed landing tables.
How Datrise loads Auth0 into ClickHouse
Datrise syncs Auth0's authentication logs, sign-ins, user identity changes, and security events into ClickHouse as a MergeTree table per source entity. Flexible or custom fields land in JSON or Map columns, and timestamps such as created, updated, and status changes are typed as DateTime64.
Sync is incremental: Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge, so re-runs update only what changed. Partition by month and order by (entity id, updated-at) for fast range scans. ClickHouse deduplicates asynchronously on merge, so Datrise uses ReplacingMergeTree and FINAL-safe queries rather than assuming immediate upserts.
Ideal for high-volume event analytics that need sub-second aggregation.
Endpoints
Auth0: Identity source for authentication and sign-in telemetry.
ClickHouse: Columnar OLAP engine for fast aggregations.
How Auth0 entities map to ClickHouse
| Auth0 entity | ClickHouse object | Notes |
|---|---|---|
| authentication logs | auth0_authentication_logs | id PK · custom fields → JSON or Map columns |
| sign-ins | auth0_sign_ins | id PK · linked to auth0_authentication_logs |
| user identity changes | auth0_user_identity_changes | DateTime64 events |
| security events | auth0_security_events | DateTime64 events |
FAQ
How does Datrise handle Auth0's custom fields in ClickHouse?
Flexible values are stored as JSON or Map columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native ClickHouse types.
How does the Auth0 to ClickHouse sync stay up to date?
It runs incrementally — Datrise uses inserts into a ReplacingMergeTree keyed on stable id, so the latest version wins on merge.
Related pipelines
More destinations for Auth0
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