IBM IBM Db2 to Looker Integration
AI-first ETL from IBM IBM Db2 into Looker. Governed entities, incremental sync, typed landing tables.
How Datrise loads IBM IBM Db2 into Looker
Datrise syncs IBM IBM Db2's tables, rows, schemas, indexes, primary keys, and change data into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.
Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.
Ideal for governed, version-controlled BI on a warehouse.
Endpoints
IBM IBM Db2: IBM relational database for transactional workloads.
Looker: Google Cloud BI with LookML semantic models and governed dashboards.
How IBM IBM Db2 entities map to Looker
| IBM IBM Db2 entity | Looker object | Notes |
|---|---|---|
| tables | db2_tables | id PK · custom fields → flattened columns (nested fields expanded for modeling) |
| rows | db2_rows | id PK · linked to db2_tables |
| schemas | db2_schemas | id PK · linked to db2_tables |
| indexes | db2_indexes | id PK · linked to db2_tables |
FAQ
How does Datrise handle IBM IBM Db2's custom fields in Looker?
Flexible values are stored as flattened columns (nested fields expanded for modeling), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker types.
How does the IBM IBM Db2 to Looker sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.
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