DatriseAI-first ETL

MoEngage Databricks SQL Warehouse

AI-first ETL from MoEngage into Databricks SQL Warehouse. Governed entities, incremental sync, typed landing tables.

How Datrise loads MoEngage into Databricks SQL Warehouse

Datrise syncs MoEngage's engagement events, campaign performance, and retention behavior signals into Databricks SQL Warehouse as a Delta Lake table per source entity. Flexible or custom fields land in VARIANT or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP.

Sync is incremental: Datrise uses a Delta MERGE on stable id, with change history available via time travel, so re-runs update only what changed. Delta partitioning by load date with OPTIMIZE/Z-ORDER on query keys. Datrise writes Unity Catalog–governed Delta tables, so lineage and permissions are managed centrally rather than per-notebook.

Ideal for lakehouse analytics and ML feature tables on Databricks.

Endpoints

MoEngage: Customer engagement source for campaigns and retention metrics.

Databricks SQL Warehouse: Lakehouse SQL endpoints over Delta tables.

How MoEngage entities map to Databricks SQL Warehouse

MoEngage entityDatabricks SQL Warehouse objectNotes
engagement eventsmoengage_engagement_eventsTIMESTAMP events
campaign performancemoengage_campaign_performanceid PK · linked to moengage_engagement_events
retention behavior signalsmoengage_retention_behavior_signalsid PK · linked to moengage_engagement_events

FAQ

How does Datrise handle MoEngage's custom fields in Databricks SQL Warehouse?

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

How does the MoEngage to Databricks SQL Warehouse sync stay up to date?

It runs incrementally — Datrise uses a Delta MERGE on stable id, with change history available via time travel.

Related pipelines

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