DatriseAI-first ETL

Onesignal to Snowflake Integration

AI-first ETL from Onesignal into Snowflake. Governed entities, incremental sync, typed landing tables.

How Datrise loads Onesignal into Snowflake

Datrise syncs Onesignal's notifications, subscribers, segments, apps, delivery events, and outcomes into Snowflake as a typed table per source entity. Flexible or custom fields land in VARIANT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP_TZ.

Sync is incremental: Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size, so re-runs update only what changed. Automatic micro-partitioning, with optional clustering keys on high-cardinality ids. Snowflake upper-cases unquoted identifiers, so Datrise standardizes on lower-case quoted names to keep column references stable.

Ideal for central analytics warehouses feeding BI and AI workloads.

Endpoints

Onesignal: Push, in-app, and email message delivery.

Snowflake: Cloud data warehouse with separated compute and storage.

How Onesignal entities map to Snowflake

Onesignal entitySnowflake objectNotes
notificationsonesignal_notificationsid PK · custom fields → VARIANT columns
subscribersonesignal_subscribersid PK · linked to onesignal_notifications
segmentsonesignal_segmentsid PK · linked to onesignal_notifications
appsonesignal_appsid PK · linked to onesignal_notifications

FAQ

How does Datrise handle Onesignal's custom fields in Snowflake?

Flexible values are stored as VARIANT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Snowflake types.

How does the Onesignal to Snowflake sync stay up to date?

It runs incrementally — Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size.

Related pipelines

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