Large Retail Case Study with Databricks: Oracle Netsuite ERP 35x Faster
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Client Context
A large retail enterprise running Oracle NetSuite ERP was processing millions of transactions daily – orders, stock movements, financial postings and operational updates.
The existing data pipeline ran overnight, from 9 PM to 5 AM, taking approximately 10 hours to complete. The pipeline could run only once per day. Any failure resulted in a 24-hour reporting delay, limiting operational visibility and slowing decision-making.
The Challenge
- Long overnight batch window
- Single daily refresh
- High operational dependency on successful batch execution
- Limited reporting agility
Our Approach
Aggranda redesigned the architecture using Databricks, implementing:
- JDBC-based ingestion from Oracle NetSuite
- Custom libraries and optimized data processing
- Production-grade orchestration with monitoring and failure alerts
- Enterprise scheduling with controlled refresh intervals
- The new architecture was built for reliability, scalability and measurable runtime performance.
Results
- Runtime reduced from 10 hours to approximately 17 minutes
- More than 35x performance improvement
- Production runtime validated at 17m 2s
- Automated hourly refresh during business days
- Near real-time operational visibility
Impact
The organization moved from a single overnight batch process to a scalable, orchestrated Databricks environment capable of supporting faster business decisions and improved reporting accuracy.
This implementation is fully running in production and represents a measurable transformation in enterprise data platform performance.