Unraveling Performance: COBOL vs. Translated Java & C# Applications Deployed on Cloud
COBOL, as a compiled language, often boasts superior performance over interpreted languages like Java and C#. However,
Java and C# were designed to excel in multi-threading and distributed processing,
leveraging the advantages of cost-effective multi-processor systems, multi-core infrastructure,
and Cloud deployments.
This article delves into performance insights for Java and C# applications derived from COBOL code translations.
MIPS: Mainframe vs. Cloud
Cloud scalability is an immense advantage. Depending on the cloud platform, whether Microsoft Azure, Amazon AWS, or a private Cloud, applications can efficiently scale processor availability and power based on demand fluctuations.
This capability largely addresses performance concerns for cloud-deployed applications.
The translation of online COBOL code to Java or C# integrates with servers like Apache-Tomcat, WebSphere, Weblogic, or Microsoft IIS. The performance usually correlates with concurrent users. The greater the user base, the higher the processor and memory demands. Yet, effective load-balancing strategies for high concurrent users have been perfected by giants like Google, Amazon, and Facebook.
VSAM / KSDS vs. SQL
SQL requests are more demanding than reading a VSAM file. Nevertheless, SQL databases present enhanced integration and maintainability. Even in COBOL, a shift from VSAM/KSDS to SQL databases has been evident. To counteract performance challenges, the translated Java/C# system should optimize database activity.
Certain COBOL features, like Packed-Decimals, variable group assignments, REDEFINE statements, and GO TO statements, need to either be omitted during Java/C# translations or be supported in the deployed application. A tailored evaluation, like a detailed usage analysis during conversion, is recommended.
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