DatriseAI-first ETL

MoEngage Amazon Redshift

AI-first ETL from MoEngage into Amazon Redshift. Governed entities, incremental sync, typed landing tables.

How Datrise loads MoEngage into Amazon Redshift

Datrise syncs MoEngage's engagement events, campaign performance, and retention behavior signals into Amazon Redshift as a typed table per source entity. Flexible or custom fields land in SUPER columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMPTZ.

Sync is incremental: Datrise uses COPY from staged files, then a delete-and-insert merge on stable id, so re-runs update only what changed. A DISTKEY on the join id and a SORTKEY on the load timestamp. Redshift performance hinges on dist/sort keys, so Datrise picks them from your entity ids and sync timestamps rather than defaulting to EVEN distribution.

Ideal for AWS-native warehouses already using the Redshift ecosystem.

Endpoints

MoEngage: Customer engagement source for campaigns and retention metrics.

Amazon Redshift: AWS petabyte-scale warehouse with Spectrum.

How MoEngage entities map to Amazon Redshift

MoEngage entityAmazon Redshift objectNotes
engagement eventsmoengage_engagement_eventsTIMESTAMPTZ 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 Amazon Redshift?

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

How does the MoEngage to Amazon Redshift sync stay up to date?

It runs incrementally — Datrise uses COPY from staged files, then a delete-and-insert merge on stable id.

Related pipelines

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