DatriseAI-first ETL

Outbrain to Sisense Integration

AI-first ETL from Outbrain into Sisense. Governed entities, incremental sync, typed landing tables.

How Datrise loads Outbrain into Sisense

Datrise syncs Outbrain's campaigns, promoted links, publishers, spend, clicks, and conversions into Sisense as modeled tables for a Sisense ElastiCube (or live connection). Flexible or custom fields land in flattened columns for the cube, and timestamps such as created, updated, and status changes are typed as date/time fields.

Sync is incremental: Datrise uses incremental ElastiCube builds on changed rows, so re-runs update only what changed. Date-partitioned facts to speed cube builds. ElastiCube is an in-memory model, so Datrise lands incremental, build-friendly tables rather than forcing full rebuilds.

Ideal for embedded analytics on an in-memory engine.

Endpoints

Outbrain: Native content discovery advertising.

Sisense: Analytics platform with elastic data models and embedded analytics.

How Outbrain entities map to Sisense

Outbrain entitySisense objectNotes
campaignsoutbrain_campaignsid PK · custom fields → flattened columns for the cube
promoted linksoutbrain_promoted_linksid PK · linked to outbrain_campaigns
publishersoutbrain_publishersid PK · linked to outbrain_campaigns
spendoutbrain_spendid PK · linked to outbrain_campaigns

FAQ

How does Datrise handle Outbrain's custom fields in Sisense?

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

How does the Outbrain to Sisense sync stay up to date?

It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.

Related pipelines

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