DatriseAI-first ETL

Polygon Stock API Sisense

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

How Datrise loads Polygon Stock API into Sisense

Datrise syncs Polygon Stock API's records, events, and configuration objects 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

Polygon Stock API: SaaS or API data source for analytics and warehouse sync.

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

How Polygon Stock API entities map to Sisense

Polygon Stock API entitySisense objectNotes
recordspolygon_stock_api_recordsid PK · custom fields → flattened columns for the cube
eventspolygon_stock_api_eventsdate/time fields events
configuration objectspolygon_stock_api_configuration_objectsid PK · linked to polygon_stock_api_records

FAQ

How does Datrise handle Polygon Stock API'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 Polygon Stock API to Sisense sync stay up to date?

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

Related pipelines

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