IBM IBM Db2 to DuckDB Integration

How Datrise loads IBM IBM Db2 into DuckDB

Datrise syncs IBM IBM Db2's tables, rows, schemas, indexes, primary keys, and change data into DuckDB as a typed table per source entity in a DuckDB file. Flexible or custom fields land in JSON or STRUCT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP WITH TIME ZONE.

Sync is incremental: Datrise uses rewrites changed entities into the local database (or Parquet) on each run, so re-runs update only what changed. Hive-partitioned Parquet by load date when exporting. DuckDB is single-writer and embedded, so Datrise produces a consistent file snapshot rather than concurrent streaming writes.

Ideal for local and notebook analytics without standing up a server.

Endpoints

IBM IBM Db2: IBM relational database for transactional workloads.

DuckDB: In-process analytics database for fast local OLAP.

How IBM IBM Db2 entities map to DuckDB

IBM IBM Db2 entity	DuckDB object	Notes
tables	`db2_tables`	id PK · custom fields → JSON or STRUCT columns
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 DuckDB?

Flexible values are stored as JSON or STRUCT columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native DuckDB types.

How does the IBM IBM Db2 to DuckDB sync stay up to date?

It runs incrementally — Datrise uses rewrites changed entities into the local database (or Parquet) on each run.

Related pipelines

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