Plausible to Sisense Integration
AI-first ETL from Plausible into Sisense. Governed entities, incremental sync, typed landing tables.
How Datrise loads Plausible into Sisense
Datrise syncs Plausible's pageviews, visitors, sessions, referral sources, goals, and page paths 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
Plausible: Privacy-friendly website traffic analytics.
Sisense: Analytics platform with elastic data models and embedded analytics.
How Plausible entities map to Sisense
| Plausible entity | Sisense object | Notes |
|---|---|---|
| pageviews | plausible_pageviews | id PK · custom fields → flattened columns for the cube |
| visitors | plausible_visitors | id PK · linked to plausible_pageviews |
| sessions | plausible_sessions | id PK · linked to plausible_pageviews |
| referral sources | plausible_referral_sources | id PK · linked to plausible_pageviews |
FAQ
How does Datrise handle Plausible'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 Plausible to Sisense sync stay up to date?
It runs incrementally — Datrise uses incremental ElastiCube builds on changed rows.
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