DatriseAI-first ETL

MoEngage DuckDB

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

How Datrise loads MoEngage into DuckDB

Datrise syncs MoEngage's engagement events, campaign performance, and retention behavior signals 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

MoEngage: Customer engagement source for campaigns and retention metrics.

DuckDB: In-process analytics database for fast local OLAP.

How MoEngage entities map to DuckDB

MoEngage entityDuckDB objectNotes
engagement eventsmoengage_engagement_eventsTIMESTAMP WITH TIME ZONE 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 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 MoEngage 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

Early access

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