IBM Db2 Consulting Services
From optimizing Db2 foundations to architecting production analytics and AI.
25+
Years of data expertise
100K+
Workloads migrated or managed
45+
Technology specializations
Pythian has a deep understanding of the full Db2 landscape
Production-ready IBM Db2 solutions for every stage of your journey.
Tune performance and reduce MIPS costs
Deep-tier Db2 performance optimization
We analyze your Db2 environment across all variants to find bottlenecks and unlock capacity—optimizing RUNSTATS, tuning query plans, reducing locking contention, and implementing MIPS reduction strategies for mainframe workloads.
Plan and execute version upgrades
End-of-support upgrade planning
With multiple Db2 versions already past end of support and Db2 11.5 LUW EOS approaching in April 2027, upgrade planning is urgent. We execute multi-step version upgrades, minimizing disruption while bringing your platform to a supported release.
Augment your DBA team
24/7 managed services and skills augmentation
The Db2 DBA talent pool is shrinking as experienced professionals retire. Pythian's managed services fill the gap with engineers who understand mainframe discipline, pureScale clustering, HADR, and the operational cadence that keeps Db2 performing.
Modernize within IBM's ecosystem
IBM modernization path
We upgrade to Db2 12.1 LUW with AI Query Optimizer and vector data, migrate to Db2 SaaS, deploy pureScale on AWS/Azure, or offload mainframe analytics to Db2 Warehouse—reducing MIPS costs while keeping transaction processing on z/OS.
Exit to cloud-native platforms
Cloud-native platform migration
We handle full exits to BigQuery, Snowflake, PostgreSQL, Databricks, and other cloud targets—including SQL PL refactoring, EBCDIC conversion, pureScale HA replacement, and application dependency analysis across the full blast radius.
Move to managed Db2 in the cloud
Managed Db2 as an intermediate step
For regulated industries that can't replace their platform in a single move, we migrate to Amazon RDS for Db2 or Db2 SaaS as a lower-risk first step—preserving code compatibility while designing an architecture that can evolve to full cloud-native later.
Modernize pipelines and orchestration
Data engineering and automation
We replace legacy ETL—DataStage, custom scripts, and JCL-based batch jobs—with modern pipelines on Airflow, Fivetran, and dbt. The migration becomes an opportunity to eliminate decades of technical debt.
Govern data and maintain compliance
Data strategy and governance
We migrate RCAC security policies to target platform equivalents and ensure compliance and regulatory reporting continuity—critical for banking, healthcare, and government customers.
Unlock analytics and AI
Production analytics and AI enablement
Transform static Cognos and QMF reports into real-time dashboards on Looker, Power BI, or Tableau, then integrate ML workflows into your new platform—moving from AI potential to production-ready performance.
Explore Pythian's database consulting services
End-to-end lifecycle management for Db2 and many more technologies.
Pythian's database consultants deliver end-to-end lifecycle management for Db2 and 45+ data technologies—from architecture design and performance tuning to migration, security, and ongoing managed services.
A phased approach to Db2 modernization that ensures migration success
Db2 estate analysis
We assess your Db2 estate across all variants, evaluating performance health, pureScale cluster status, and end-of-support exposure. For unsupported versions, we build a stabilization plan to keep mission-critical workloads running while we plan the path forward.
Build a complete picture for your data modernization
We catalog every workload, pipeline, and security policy, then map the dependencies—including application code, transaction integrations, ETL pipelines, and reports. This complete picture is where most modernization programs fail without deep platform expertise.
ROI-focused modeling
We recommend the right path—IBM modernization, cloud-native exit, managed intermediate step, or phased hybrid—based on your workloads and priorities. Vendor-neutral guidance grounded in ROI modeling, not vendor loyalty.
Migrating while maintaining data integrity
We execute end to end: SQL PL refactoring using automated conversion tools accelerated by expert manual rewrite, petabyte-scale data extraction with EBCDIC conversion, dual-run synchronization via CDC, and hash-based data reconciliation to guarantee integrity.
24/7 data ecosystem support
We provide 24/7 managed services for legacy Db2 during transition and cloud platforms after migration. As your DBA workforce retires, Pythian fills the gap with engineers who understand both worlds.
Ready to transform your IBM Db2 environment?
Pythian's related IBM Db2 services
End-to-end data services ensure your Db2 modernization delivers lasting business value.
Build resilient, modern pipelines
Data engineering consulting
We replace fragmented Db2 ETL—DataStage, Informatica, and JCL-based batch jobs—with resilient, observable data flows built on Airflow, Fivetran, dbt, and cloud-native orchestration.
Deliver real-time insights
Production analytics
From static Cognos and QMF batch reports to real-time insights on Looker, Power BI, and Tableau. Business users get answers in seconds, not the hours that mainframe batch extracts typically require.
Operationalize AI at scale
Production AI
From data locked in mainframe Db2 to production-ready AI. We integrate ML workflows using BigQuery ML, Vertex AI, Snowpark, or Databricks ML—deploying fraud detection, risk models, and GenAI capabilities that legacy Db2 couldn't support.
IBM Db2 consulting services frequently asked questions (FAQ)
Security is built into every phase of our migration process. We start with a comprehensive audit of your existing Db2 security architecture—including RCAC (Row and Column Access Control) policies, LBAC (Label-Based Access Control) on z/OS, and existing audit configurations. During migration, we map these fine-grained security policies to their equivalents on the target platform—whether that's row-level security in PostgreSQL, BigQuery column-level access controls, or Snowflake data masking policies. For mainframe exits, we ensure EBCDIC-to-UTF-8 data conversion preserves data integrity across all character sets. Dual-run validation confirms that security coverage is identical on both platforms before cutover. We maintain regulatory reporting continuity throughout—critical for organizations where a gap in compliance isn't acceptable.
ROI from Db2 modernization comes from multiple sources. Mainframe MIPS cost reduction is often the most immediate win—offloading analytics workloads from z/OS to cloud platforms can deliver MIPS savings. Beyond cost reduction, organizations see significant query performance improvements on modern cloud targets, dramatic reductions in operational complexity, and the ability to enable self-service analytics and production AI that were impossible with legacy Db2 batch extracts. Eliminating IBM Db2 Enterprise licensing on distributed platforms provides additional savings. The phased approach we recommend means you start seeing returns on high-value workloads early in the migration.
Automated conversion tools—SnowConvert for DB2, Next Pathway SHIFT, SQLines, and db2topg—can typically handle 60 to 80 percent of standard SQL conversion. However, complex SQL PL stored procedures with Db2-specific extensions, MQT (materialized query table) dependencies, and embedded SQL in COBOL or Java applications require expert manual refactoring. PL/SQL compatibility mode code (adopted by some organizations for Oracle-to-Db2 migrations) requires different migration treatment than native SQL PL. This layered complexity is precisely where Pythian's deep Db2 expertise makes the difference—we've refactored complex procedural logic across all three Db2 variants and know where the hidden dependencies live.
It depends on your deployment context, workload characteristics, risk tolerance, and strategic direction. IBM is aggressively investing in Db2's future—Db2 12.1 LUW with AI Query Optimizer and vector data, pureScale on AWS/Azure, and Db2 SaaS are legitimate modernization paths for organizations deeply embedded in the IBM ecosystem. Amazon RDS for Db2 offers a managed intermediate step that preserves code compatibility while eliminating operational overhead. Cloud-native platforms like BigQuery, Snowflake, or PostgreSQL are better suited for organizations ready to fully decouple from IBM and gain serverless scaling, modern BI integration, and AI-ready infrastructure. A phased approach—moving analytics to cloud-native first while keeping transaction processing on Db2—lets you reduce risk and prove value before committing to a full exit. Pythian provides vendor-neutral assessment based on workload analysis and ROI modeling, not vendor relationships.
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