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
Broadcom contract changes forced immediate cost hikes
A tight 12-month Broadcom renewal threatened to triple infrastructure costs while fixed Greenplum capacity limits forced DBAs to manually tune distribution keys and GPORCA query plans daily to manage severe data skew.
Heavily tangled legacy systems lacked any documentation
The database environment was tightly knotted across 400+ complex PL/pgSQL stored procedures, 75 fragile gpfdist pipelines, and Informatica workflows bound to Greenplum external tables without any existing migration playbooks or documentation.
Outdated software limits halted critical fraud tracking
High-priority fraud scoring updates remained completely blocked because the legacy Apache MADlib software could not scale with a 40% transaction volume surge or integrate with modern machine learning tools.
Slow regulatory reporting triggered audit risks
Quarter-end risk validation checks dragged on for four hours instead of minutes because the legacy infrastructure choked during peak transaction surges, causing dangerous reporting delays that financial regulators explicitly flagged.
Converting legacy code permanently wiped out data imbalances for the bank's team.
Pythian automated the translation of 85% of the bank's 400+ legacy PL/pgSQL stored procedures into standard BigQuery SQL. Engineers manually converted the remaining complex Greenplum distribution keys and GPORCA query plans into BigQuery partitioned and clustered tables, permanently eliminating the data skew that previously required a full-time DBA.
A safe parallel data transfer protected daily operations from any downtime.
Engineers bypassed restrictive on-premises gpfdist utilities to securely stream 200 terabytes of historical compliance records into Google Cloud Storage with zero business disruption. A strict four-week dual-run validation phase operated Greenplum and BigQuery side by side, guaranteeing absolute data accuracy while beating the 12-month Broadcom contract deadline.
Modern fraud models successfully captured over eight million dollars in risk.
The team uncoupled legacy Apache MADlib models from restrictive physical hardware to rebuild them on Vertex AI. This allowed fraud detection algorithms to scale dynamically alongside a 40% volume surge, capturing $8.2M in suspicious transactions within six months and funding a migration that saved $3.1M annually by avoiding Broadcom renewal fees.
A complete pipeline overhaul gave hundreds of analysts instant access to data.
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.
.svg){kind=small}
.svg){kind=small}