DatriseAI-first ETL

Source Dynamodb Sisense

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

How Datrise loads Source Dynamodb into Sisense

Datrise syncs Source Dynamodb'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

Source Dynamodb: SaaS or API data source for analytics and warehouse sync.

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

How Source Dynamodb entities map to Sisense

Source Dynamodb entitySisense objectNotes
recordssource_dynamodb_recordsid PK · custom fields → flattened columns for the cube
eventssource_dynamodb_eventsdate/time fields events
configuration objectssource_dynamodb_configuration_objectsid PK · linked to source_dynamodb_records

FAQ

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

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

Related pipelines

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