DatriseAI-first ETL

RSS to Sisense Integration

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

How Datrise loads RSS into Sisense

Datrise syncs RSS's feed items, titles, links, publication dates, authors, and categories 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

RSS: Syndicated feed items from publishers and blogs.

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

How RSS entities map to Sisense

RSS entitySisense objectNotes
feed itemsrss_feed_itemsid PK · custom fields → flattened columns for the cube
titlesrss_titlesid PK · linked to rss_feed_items
linksrss_linksid PK · linked to rss_feed_items
publication datesrss_publication_datesid PK · linked to rss_feed_items

FAQ

How does Datrise handle RSS'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 RSS to Sisense sync stay up to date?

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

Related pipelines

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