IBM IBM Db2 to Snowflake Integration

How Datrise loads IBM IBM Db2 into Snowflake

Datrise syncs IBM IBM Db2's tables, rows, schemas, indexes, primary keys, and change data into Snowflake as a typed table per source entity. Flexible or custom fields land in VARIANT columns, and timestamps such as created, updated, and status changes are typed as TIMESTAMP_TZ.

Sync is incremental: Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size, so re-runs update only what changed. Automatic micro-partitioning, with optional clustering keys on high-cardinality ids. Snowflake upper-cases unquoted identifiers, so Datrise standardizes on lower-case quoted names to keep column references stable.

Ideal for central analytics warehouses feeding BI and AI workloads.

Endpoints

IBM IBM Db2: IBM relational database for transactional workloads.

Snowflake: Cloud data warehouse with separated compute and storage.

How IBM IBM Db2 entities map to Snowflake

IBM IBM Db2 entity	Snowflake object	Notes
tables	`db2_tables`	id PK · custom fields → VARIANT 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 Snowflake?

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

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

It runs incrementally — Datrise uses staged loads merged on stable id with MERGE, so credits scale with change volume, not table size.

Related pipelines

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