International Journal For Multidisciplinary Research

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Optimizing Oracle to SAP HANA Migration for Performance and Scalability: A Case Study on SAP SuccessFactors Learning

Author(s) Pradeep Kumar
Country United States
Abstract This research paper explores the migration of the SAP SuccessFactors Learning application from Oracle DB to SAP HANA DB, focusing on the challenges, performance optimizations, and outcomes of this transition. SAP SuccessFactors Learning, originally designed on Oracle’s row-based RDBMS, embedded extensive business logic within PL/SQL procedures, functions, and triggers. The application’s architecture was tightly coupled with Oracle SQL syntax and transactional operations, making direct migration to SAP HANA, a columnar, in-memory database, complex and performance-intensive.
Key migration challenges included SQL incompatibility, inefficient query performance, and scalability bottlenecks due to HANA’s parallel, read-optimized execution model. Oracle-specific features like non-equijoins, dynamic SQL handling, and complex indexing strategies did not translate directly to HANA's architecture.
To address these issues, a dynamic SQL conversion framework was developed to transform Oracle SQL queries to HANA-compatible syntax in real-time. Additionally, caching mechanisms for query optimization and large-page memory tuning were implemented to reduce CPU usage and enhance execution times. As a result, the migration achieved a 40% reduction in query execution time, a 30% decrease in CPU utilization, and improved scalability.
This study highlights effective strategies for optimizing performance and scalability in large-scale enterprise application migrations to in-memory databases like SAP HANA.
Keywords Database migration, SQL optimization, In-memory database, SAP HANA, Scalability improvements
Field Engineering
Published In Volume 3, Issue 5, September-October 2021
Published On 2021-09-04
DOI https://doi.org/10.36948/ijfmr.2021.v03i05.37537
Short DOI https://doi.org/g85snr
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E-ISSN 2582-2160
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