DB Databricks Financial Services Central and Eastern Europe

Raiffeisen Bank International

Data Lake / Data Warehouse Modernization · Security and Compliance · System Migration

Raiffeisen Bank International (RBI) operates a highly federated network of banks across many countries with stringent European banking requirements for security, governance, and auditability. Decades of organic growth left a fragmented analytics environment of on-prem and cloud systems with their own SQL dialects, access controls, and operational models — limiting collaboration, code reuse, and group-level governance, with one query taking 30 days on the legacy infrastructure.

5x analytics TCO reduction vs. previous cloud solution
Hundreds of concurrent users across risk, compliance, finance, retail analytics
Legacy query reduced from 30 days to ~12 minutes
~30–40% faster time to insight

Solution

Raiffeisen Bank International consolidated a fragmented analytics environment — on-premises and cloud systems with different SQL dialects, access controls, and operational models across federated banks in Central and Eastern Europe — into the APEX decentralized analytics platform built on Databricks SQL. The rollout was deliberately phased: legacy platforms ran in parallel while users were onboarded gradually and production workloads were protected. Once on Databricks SQL, queries that previously took up to 30 days dropped to ~12 minutes, average workloads run 3–4x faster, and BI is served directly from the Lakehouse without unnecessary data movement. Elastic compute scales on demand for hundreds of concurrent risk, compliance, finance, and retail analysts. Centralized access controls, audit logs, and lineage meet stringent European banking governance requirements, while open formats and APIs avoid future lock-in.

Data flow

RBI consolidated a fragmented analytics environment — on-prem and cloud systems with different SQL dialects across federated banks in Central and Eastern Europe — into the APEX decentralized analytics platform on Databricks SQL. Legacy platforms ran in parallel during onboarding so production workloads were protected. BI workloads are now served directly from the Lakehouse without unnecessary data movement, and an internal cost-monitoring platform on Databricks tracks usage by warehouse, user, and workload. Centralized access controls, audit logs, and lineage support stringent European banking governance requirements.

Solution architecture

1 components · 1 layer
  1. Serving
    • Databricks SQL Unified SQL warehouse running the APEX analytics platform; serves hundreds of concurrent users across risk, compliance, finance, and retail analytics with elastic compute scaling on demand, plus centralized access controls, audit logs, and lineage for European banking compliance

Architecture clues

  • APEX decentralized analytics platform integrating Databricks SQL
  • Automated cluster shutdowns and centralized operations
  • Centralized access controls, audit logs, and lineage in Databricks SQL
  • Elastic compute scaled on demand for large analytical jobs
  • Internal cost-monitoring and forecasting platform built on Databricks
  • Open formats and APIs to avoid vendor lock-in
  • Phased parallel-run migration from legacy systems

Evidence from the source

5x Analytics TCO reduction compared to the previous cloud solution
Average workloads now run three to four times faster compared to our previous cloud solution
we had queries that were taking 30 days within our legacy infrastructure, and with Databricks SQL, we reduced them to about 12 minutes