Heroku to Sisense Integration
AI-first ETL from Heroku into Sisense. Governed entities, incremental sync, typed landing tables.
How Datrise loads Heroku into Sisense
Datrise syncs Heroku's apps, dynos, releases, add-ons, config vars, and build logs 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
Heroku: Application platform with dynos and add-ons.
Sisense: Analytics platform with elastic data models and embedded analytics.
How Heroku entities map to Sisense
| Heroku entity | Sisense object | Notes |
|---|---|---|
| apps | heroku_apps | id PK · custom fields → flattened columns for the cube |
| dynos | heroku_dynos | id PK · linked to heroku_apps |
| releases | heroku_releases | id PK · linked to heroku_apps |
| add-ons | heroku_add_ons | id PK · linked to heroku_apps |
FAQ
How does Datrise handle Heroku'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 Heroku to Sisense sync stay up to date?
It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.
Related pipelines
More destinations for Heroku
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