DatriseAI-first ETL

IBM IBM Db2 to Sisense Integration

AI-first ETL from IBM IBM Db2 into Sisense. Governed entities, incremental sync, typed landing tables.

How Datrise loads IBM IBM Db2 into Sisense

Datrise syncs IBM IBM Db2's tables, rows, schemas, indexes, primary keys, and change data 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

IBM IBM Db2: IBM relational database for transactional workloads.

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

How IBM IBM Db2 entities map to Sisense

IBM IBM Db2 entitySisense objectNotes
tablesdb2_tablesid PK · custom fields → flattened columns for the cube
rowsdb2_rowsid PK · linked to db2_tables
schemasdb2_schemasid PK · linked to db2_tables
indexesdb2_indexesid PK · linked to db2_tables

FAQ

How does Datrise handle IBM IBM Db2'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 IBM IBM Db2 to Sisense sync stay up to date?

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

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