Greenplum Consulting Services
From optimizing Greenplum foundations to architecting data-driven analytics.
25+
Years of data expertise
100K+
Workloads migrated or managed
45+
Technology specializations
Greenplum services that keep your business running during transformation
Stabilize
Greenplum environment assessment
We assess your cluster health to identify what's broken or bleeding cost under Broadcom's restructured licensing. You get a benchmarked baseline and a clear picture of your options.
Optimize
Performance tuning and operational support
We tune distribution policies, GPORCA query plans, resource groups, and VACUUM strategies to extract maximum performance from your current cluster. We keep your environment stable while you plan your next move.
Migrate and modernize
Cloud-native platform migration
We handle the full migration to Snowflake, BigQuery, Databricks, or Redshift. Your modernized platform unlocks analytics and other capabilities that weren't feasible on legacy Greenplum.
How we work with you
Identifying optimization opportunities
We assess cluster health—distribution keys, GPORCA behavior, resource groups, and segment utilization. For clusters under Broadcom pressure, we identify optimization opportunities and provide a renewal cost analysis to clarify your financial options.
Mapping your modernization
We recommend the right path—cloud-native exit, Broadcom modernization, or phased hybrid—based on your workloads and priorities. Vendor-neutral guidance grounded in TCO modeling, not vendor loyalty.
Migrating toward automation
Code conversion, distribution policy remapping, gpfdist replacement, and MADlib migration to cloud-native ML—leveraging PostgreSQL compatibility for higher automation rates. Our engineers focus on the complex work that tools like BigQuery Migration Service and SnowConvert AI can't handle.
Rigorous confirmation of data integrity
Parallel extraction across Greenplum segments for multi-terabyte to petabyte data movement. Dual-run synchronization and rigorous reconciliation validate data integrity before cutover.
Ongoing empowerment of business intelligence
We reconnect BI tools to your new platform, migrate MADlib models to production ML, and provide 24/7 ongoing support so your team focuses on value, not infrastructure.
Modernizing from Greenplum for mission-critical analytics for a global financial institution
From Broadcom-pressured Greenplum to AI-ready cloud analytics.
A tier-1 financial institution running 200+ terabytes of regulatory analytics on VMware Tanzu Greenplum faced a licensing crisis after Broadcom's acquisition. Renewal costs were set to triple. The board demanded next-generation fraud detection. Pythian migrated the entire MPP environment to Google BigQuery—cutting total cost of ownership, eliminating vendor lock-in, and delivering production-ready AI within nine months.
Pythian: The enterprise migration leader
Modern platform migrations from Greenplum
Snowflake
Migrate Greenplum data warehouses to Snowflake’s Data Cloud to eliminate hardware dependencies and support elastic, high-concurrency analytics workloads.
Databricks
Transition Greenplum analytics workloads to the Databricks Lakehouse platform for unified data engineering, machine learning, and BI analytics.
Redshift
Move Greenplum clusters to Amazon Redshift to gain managed infrastructure, scalable compute, and integration with the AWS ecosystem.
Ready to navigate the Broadcom transition?
Pythian's related Greenplum services
Integrated expertise across every layer of the data stack.
Stabilize and optimize legacy systems
Database consulting
Deep-tier PostgreSQL and MPP expertise across legacy Greenplum and cloud-native platforms. We keep mission-critical clusters running at peak reliability during transition.
Govern and control your data estate
Data strategy and governance
Secure, compliant, and cost-controlled environments—with data ownership policies, cloud-native IAM alignment, and a long-term data roadmap.
Deliver real-time insights
Data-driven analytics
From static Cognos and MicroStrategy reports to real-time insights on Looker, Power BI, and Tableau. BI reconnection and validation that's invisible to business users.
Greenplum consulting services frequently asked questions (FAQ)
Security is built into every phase of our migration process. We start with a comprehensive assessment of your existing Greenplum security model—role-based access controls, row-level security policies, and encryption configurations. During migration, we remap these controls to cloud-native IAM frameworks (GCP IAM, AWS IAM, Azure AD), preserving the access policies that regulated industries depend on. For organizations in financial services or government, we design dual-run validation architectures that ensure no gaps in compliance coverage during the transition. Data governance metadata is migrated to modern platforms like Google Dataplex, Unity Catalog, or Collibra, so your audit trail remains intact.
The ROI from Greenplum modernization comes from multiple sources. The most immediate win is licensing cost reduction—customers facing Broadcom's restructured pricing see significant reductions in the total cost of ownership by moving to cloud-native platforms. Beyond cost savings, organizations gain elastic scaling that eliminates the complexity of gpexpand operations, improved query performance on modern columnar engines, and the ability to support real-time analytics, semi-structured data, and production AI capabilities that legacy Greenplum couldn't deliver. The PostgreSQL compatibility advantage also means higher automation rates during SQL conversion, which reduces migration timeline and cost compared to exits from proprietary platforms like Teradata or Netezza.
Greenplum's PostgreSQL foundation is a genuine migration advantage here. SQL and PL/pgSQL code conversion to PostgreSQL-compatible targets (AlloyDB, Aurora PostgreSQL) achieves the highest automation rates—significantly higher than migrations from proprietary platforms like Teradata or Netezza. For non-PostgreSQL targets like BigQuery or Snowflake, tools like Google's BigQuery Migration Service and Snowflake's SnowConvert AI handle a large portion of standard SQL translation automatically. However, MPP-specific constructs—distribution policy logic, GPORCA-tuned query patterns, external table definitions, and gpfdist pipeline orchestration—require manual refactoring by engineers who understand both the source and target architectures. MADlib in-database ML models have no automated conversion path and must be rebuilt on platform-native ML tools. This is exactly where Pythian's dual fluency in PostgreSQL heritage and MPP complexity makes the difference.
It depends on your workload characteristics, regulatory requirements, and strategic direction. Exiting to a cloud-native platform (BigQuery, Snowflake, Databricks) is the right choice for most organizations—you gain elastic scaling, modern analytics capabilities, transparent pricing, and freedom from vendor lock-in risk. However, staying within the Broadcom ecosystem makes sense for organizations with specific regulatory compliance or data sovereignty requirements that mandate on-premises control. In that case, we help you upgrade to Greenplum 7.x, deploy on Kubernetes via the Greenplum Operator, and optimize your licensing position. A third option—phased hybrid—lets you migrate high-value workloads to cloud-native platforms first while maintaining Greenplum for workloads with specific on-premises requirements. Pythian provides vendor-neutral assessment based on TCO analysis and business outcomes, not vendor pressure.
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