Modernizing a legacy Greenplum cluster into a BigQuery data warehouse saved $3.1M.
Pythian migrated 200 terabytes of data from Greenplum to BigQuery to establish a scalable foundation.
A multinational financial institution running 200 terabytes of regulatory analytics on a legacy Greenplum cluster faced an immediate crisis when vendor licensing shifts threatened to triple their infrastructure costs. Beyond these commercial pressures, unoptimized query plans and rigid data pipelines stalled high-priority fraud detection updates. Seeking to eliminate this rigid vendor lock-in, the organization partnered with Pythian to modernize their database environment on Google BigQuery. Pythian practitioners successfully migrated the entire estate within nine months, eliminating processing delays so internal risk analysts could run complex exposure models instantly.
Pythian's dual fluency in legacy database limitations and complex cloud architectures allowed us to secure complete data sovereignty while building a scalable foundation for modern analytical tools."
Chief Information Officer
Financial Institution
$3.1M
Annual infrastructure savings
60%
Reduction in total cost of ownership
99.9%
Platform availability post-migration
Accelerate your Greenplum migration to unlock cloud analytics performance.
The tier-1 bank was constrained by analytics bottlenecks from their legacy Greenplum MPP environment.
Pythian engineered a secure migration path to transition the bank’s reporting portfolios to an elastic cloud data platform.
Our legacy MPP cluster simply could not keep pace with our growing analytics demands, but Pythian operated as an extension of our team to engineer a secure cloud migration path that completely eliminated our processing bottlenecks."
Chief Information Officer
Financial Institution
Restructured Broadcom licensing forced cost escalations
Restructured enterprise pricing and fixed capacity limits unique to the on-premises cluster forced immediate Tanzu Data Suite cost escalations while DBAs manually managed data skew and distribution keys to maintain daily operations.
Monolithic legacy dependencies lacked a clear exit plan
The database architecture was deeply coupled across more than 400 PL/pgSQL stored procedures, 75 gpfdist pipelines, and Informatica workflows bound to Greenplum external tables with zero existing documentation or migration playbooks.
Legacy software limitations stalled high-priority fraud detection
Advanced predictive risk modeling and fraud scoring updates remained completely stalled due to legacy Apache MADlib software limitations and unoptimized GPORCA query optimizer performance.
Delayed regulatory reporting triggered audit exposure risks
Quarter-end risk validation took hours instead of minutes because legacy models failed to scale with a 40 percent surge in transaction volume. This left risk analysts waiting days for exposure data—a gap regulators flagged while the board's production AI mandate remained stalled.
Legacy Greenplum PL/pgSQL code was translated into standard BigQuery SQL.
Pythian automated the translation of over 400 legacy PL/pgSQL stored procedures by 85%. Technical teams manually refactored the remaining complex Greenplum distribution keys and GPORCA query plans into BigQuery partitioned tables, permanently eliminating the data skew that previously consumed a full-time DBA.
Historical transaction data was extracted without legacy gpfdist bottlenecks.
Engineers bypassed restrictive legacy gpfdist utilities to securely stream 200 terabytes of historical records to the cloud with zero downtime. A strict four-week dual-run validation phase ran Greenplum and BigQuery side by side to ensure absolute data parity and beat the 12-month Broadcom renewal deadline.
In-database Apache MADlib models were rebuilt on Vertex AI.
The team uncoupled legacy Apache MADlib models from restrictive database hardware to deploy Vertex AI fraud detection into production, scaling easily alongside a 40% volume surge. This unlocked the stalled AI mandate, identifying $8.2M in suspicious transactions in six months while funding a migration that saved $3.1M annually by avoiding the Broadcom renewal.
Legacy BI tools and pipelines were modernized with Airflow, dbt, Fivetran, and Looker.
Technical teams replaced 75 legacy pipelines with an Airflow, dbt, and Fivetran stack, moved reporting to Looker, and reconnected Tableau for 500+ analysts—cutting a three-day queue to instant self-service. Dataplex lineage tracking reduced audit prep by 70%, slashing quarter-end reporting from four hours to 22 minutes before transitioning to 24/7 managed services.
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