Enterprise Database Consolidation with Exadata: A Real-World Case Study

Database Consolidation with Exadata

Keywords: Oracle database consolidation, Exadata Cloud@Customer, performance tuning, CDB/PDB, Oracle RAC, capacity planning

This post is based on notes from one of my migration projects for a major financial institution. The institution aimed to simplify its sprawling on-premise database landscape with an ambitious goal: to consolidate over 500 critical Oracle databases onto Exadata Cloud@Customer (ExaCC) with minimal disruption. This was a multi-faceted and multi phased project and this migration was part of one phase only.


Initial Challenges

Before the transformation, the IT environment was fragmented:

  • 200+ non-CDB 12c instances across scattered bare-metal servers
  • Licensing overhead from underutilized hardware
  • End-of-support risks for Oracle 12.1
  • Poor CPU/memory utilization and inconsistent backups
  • Performance spikes during peak windows

Sizing & CPU Planning Strategy

Proper sizing was important part to avoid oversubscription. The approach followed was:

  • Collected peak 8-hour CPU stats (avg. 70% of 8 vCPUs per DB)
  • Added a diversity factor (typically 0.6–0.7 for mixed workloads)
  • Considered consolidation overhead (~15%)
  • Accounted for PDB/tenant isolation
  • Calculated total vCPU requirement and mapped to ¼ rack ExaCC (X9M)

The base line or example calculation used: 100 CDBs with 3 PDBs each → ~400 vCPU consolidated → 2 x ¼ rack ExaCC nodes (based on max 112 OCPUs per node)


Migration Strategy

Tools Used:

  • RMAN for full/incremental backup migration
  • Oracle Data Pump for schema lift & shift
  • Cross Platform Transportable Tablespaces
  • Oracle Golden-Gate for live replication (for custom schema and zero downtime requirement)

Architecture Evolution:

  • Shift to Container Databases (CDB)
  • High Availability with Oracle RAC & Data Guard
  • Centralized patching, backups, and monitoring

Post-Migration Gains

  • 30% lower licensing cost via CPU pooling and CDB structure
  • Performance boosted: Avg. query times reduced by 40%
  • Simplified hybrid cloud management with ExaCC
  • Security & compliance with encrypted backups, audit trails, and restricted access zones

My Important Takeaways

  • Used performance-based sizing, not 1:1 lift-and-shift
  • CDB/PDB model helps maximize consolidation
  • Combine diversity factor + overhead buffer for safe capacity planning
  • ExaCC is ideal for regulated environments needing on-premise control + cloud agility

Got a similar project in mind? Contact me via LinkedIn or leave a comment!

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