DB2 → SNOWFLAKE
Modernize DB2 to Snowflake without carrying legacy complexity forward.
Datachecks combines AI-driven estate analysis, source-to-target mapping, SQL and procedural translation, validation, and reconciliation with expert review for complex DB2-to-Snowflake modernization programs.
Supported objects and automation depth vary by source, target, and migration scope.
THE MIGRATION CHALLENGE
DB2 → Snowflake requires more than moving legacy tables.
Years of DB2 schemas, SQL, procedures, data types, dependencies, transformations, and platform-specific behavior must be understood and translated into a Snowflake-native target.
1
Automated with review
Legacy schema and data types
DB2 types, precision rules, character handling, temporal values, defaults, generated values, and schema conventions require deliberate target mappings rather than blind conversion.
2
Accelerated translation
DB2 SQL differences
DB2-specific functions, SQL syntax, date handling, recursive patterns, special registers, and other platform-specific constructs need Snowflake-aware translation.
3
Expert review
Procedural logic
Stored procedures, functions, triggers, compound SQL, dynamic statements, and legacy business logic may require automated translation plus targeted expert intervention.
4
Automated discovery
Long-lived dependencies
Mature DB2 estates often have layers of views, jobs, reporting logic, downstream extracts, procedures, and applications built around the same objects over many years.
5
Human-owned
Historical transformation rules
Business transformations, cleansing logic, historical exceptions, and undocumented implementation patterns can be embedded across code and data, making discovery essential before conversion.
6
Automated
Migration verification
Large legacy estates need systematic source-target comparisons across data, transformations, aggregates, and business-critical outputs before DB2 can safely be retired.
HOW DATACHECKS HELPS
Understand. Map. Translate. Validate.
The migration is executed through controlled agent workflows, with migration experts reviewing ambiguity, unsupported patterns, business rules, and critical exceptions.
01 · UNDERSTAND
Assessment + Discovery
Build a complete view of the DB2 estate.
Inventory schemas, tables, views, routines, dependencies, and data patterns; identify high-complexity objects and establish migration scope.
Migration-ready DB2 estate assessment
02 · MAP
Source → Target Mapping
Generate DB2-to-Snowflake mappings.
Map tables, columns, data types, transformation rules, and target structures while surfacing ambiguous mappings for expert review.
Reviewed Snowflake mappings
03 · TRANSLATE
SQL + Procedural Translation
Accelerate DB2 SQL and routine conversion.
Translate supported DB2 SQL and procedural logic into Snowflake-compatible target patterns and route unsupported or architecture-sensitive constructs for review.
Target-ready logic with exceptions surfaced
04 · VALIDATE
Testing + Reconciliation
Reconcile DB2 and Snowflake before cutover.
Generate tests, compare source and target results, validate transformations, reconcile critical datasets, and investigate mismatches before retiring the legacy platform.
Validated Snowflake outputs with migration evidence
MIGRATION EVIDENCE
Every stage leaves behind something your team can review.
SOURCE → TARGET MAPPING
CUSTOMER_ID DECIMAL(18,0) → CUSTOMER_ID NUMBER(18,0)
TRANSFORMATION: TRIM + UPPER · CONFIDENCE 97% · REVIEWED
TRANSLATION
DB2 SQL → Snowflake SQL
TRANSLATED · VALIDATED
EXCEPTION
Legacy routine with platform-dependent behavior
EXPERT REVIEW REQUIRED
DELIVERY TIME
Compress months of DB2 modernization work into weeks.
Automate legacy-estate analysis, mappings, repetitive SQL conversion, test generation, and reconciliation while migration experts focus on complex routines and architecture-sensitive decisions.
TRADITIONAL MIGRATION
MONTHS
Understand
Map
Translate
Test & validate
Reconcile
Cutover
WITH DATACHECKS
WEEKS
Understand
Map
Translate + test
Validate + reconcile
Cutover
Why the timeline shrinks: automated estate analysis · generated mappings · accelerated SQL translation · generated tests · automated reconciliation. Bar lengths are illustrative, not project commitments.
MIGRATION CONFIDENCE
Validate Snowflake before switching off DB2.
Compare migrated datasets and transformed outputs against DB2, reconcile critical measures, and resolve exceptions before production cutover and legacy retirement.
TRANSLATE
TEST ✓
TARGET LOAD
VALIDATE ✓
RECONCILE ✓
EXCEPTIONS REVIEWED ✓
READY FOR CUTOVER
HUMAN IN THE LOOP
Automate the repeatable work. Keep experts on the decisions.
AGENT EXECUTION
Estate inventory · metadata analysis · profiling · standard mappings · common SQL translation · test generation · row-count checks · aggregate comparisons
EXPERT REVIEW
Ambiguous mappings · unsupported procedural patterns · complex logic · unusual transformation patterns · reconciliation discrepancies
HUMAN-OWNED
Business-rule interpretation · critical exception resolution · acceptance criteria · migration scope decisions · cutover approval
ENTERPRISE DEPLOYMENT
Run the migration engine where the data lives.
Deploy Datachecks within enterprise-controlled infrastructure, connect approved AI models, and keep migration data, metadata, execution, and evidence inside your security boundary.
Private Deployment
BYOM
SAML SSO
SOC 2
ISO 27001
RELATED RESOURCES
Go deeper on this migration.
PLANNING THIS MIGRATION?
Start with the estate you already have.
Share your source environment, target architecture, approximate object volumes, and migration goals. We’ll help identify complexity, scope, and where automation can remove manual delivery work.
Useful to bring: source schemas · object counts · procedural code volume · target architecture · timelines