Mainframe
COBOL to Java, C#
& Cloud
Many financial institutions still rely on IBM mainframes for core banking and transaction systems. These platforms are stable and proven, but they carry high annual operating costs driven by licensing, MIPS-based billing, and infrastructure support.
When planning modernization, organizations typically compare two main paths:
AWS offers a managed runtime with reduced on-premise infrastructure, but long-term costs depend on cloud usage. SoftwareMining provides automated COBOL to Java translation with full hosting flexibility, enabling deployment on-premise or in any cloud while minimizing vendor lock-in and keeping annual support predictable.
The table below compares key cost and operational factors for IBM mainframes, AWS Mainframe Modernization, SoftwareMining, and IBM watsonx for a typical medium size system.
The values focus on translation and runtime cost differences. In most modernization projects, testing and validation remain the largest overall cost, often exceeding translation by several times.
| Category | IBM Mainframe (CICS-based) | SoftwareMining - COBOL to Java Modernization | AWS Mainframe Modernization | IBM watsonx-based Modernization |
|---|---|---|---|---|
| Translation / Modernization Fee | Not applicable |
Per-line pricing model based on application size
(overall cost strongly influenced by testing effort) |
Cloud-based modernization with usage-based billing
(translation fee is small compared to testing) |
AI-driven modernization with token and model usage costs
(AI translation cost is minor relative to testing) |
| Typical Annual Runtime Cost |
Greater than $1M per year
(CICS, MIPS, and licensing) |
Approximately 10 to 20 percent of typical mainframe runtime cost
(client-managed hosting; ASM support only) |
Combination of modernization software and cloud usage,
typically 30 to 70 percent of mainframe runtime cost
(varies by workload and AWS services used) |
Generally 25 to 75 percent of mainframe runtime cost,
depending on model usage and cloud consumption
(AI model calls, storage, and hybrid runtime) |
| Cloud Hosting and Runtime Flexibility | Fixed mainframe infrastructure | Client-controlled: on-prem, private or public cloud | Runs on AWS cloud only | IBM Cloud or hybrid (limited exit options) |
| Support Model | Vendor managed SLAs | Annual SLA-based support (tool and runtime libraries) | Tiered AWS and partner support | IBM Cloud support tiers; standard cloud SLAs |
| Cost Predictability | High fixed cost (MIPS-based) | Stable per-LOC + predictable ASM tiers | Variable (usage-based cloud billing) | Variable (model usage, cloud runtime, token costs) |
| Vendor Lock-in Risk | Very high (mainframe platform dependency) | Low (portable Java runtime) | High (AWS ecosystem dependency) | Medium-High (IBM ecosystem and AI service dependency) |
The values shown are approximate industry ranges provided for comparison purposes only. Actual IBM and AWS pricing varies based on licensing terms, workload volume, and cloud usage.
While cloud modernization offers clear benefits, it is important to consider long-term lock-in risks. AWS Mainframe Modernization often generates applications that rely on AWS-native orchestration, storage, and runtime components. IBM watsonx, although described as hybrid-cloud capable, depends on IBM Cloud services, AI runtime models, and proprietary data pipelines. Moving an AI-assisted or cloud-managed system to another provider may require significant rework, retesting, and architectural change.
In contrast, SoftwareMining produces clean Java code that runs on any Java-compliant platform. The translated application depends only on standard Java and a stable set of SoftwareMining runtime libraries that are delivered with the project, rather than on cloud-native services or proprietary platform features.
Hosting is fully client-controlled, whether on-prem, private cloud, or public cloud. Annual ASM support covers the translation tool and runtime libraries, but there is no usage-based runtime licensing and no requirement to run on a specific cloud provider. This gives organizations far greater control over infrastructure strategy, cost management, and long-term freedom than mainframe- or cloud-managed modernization options.
Translation is usually only a small portion of a modernization project. The largest cost is regression testing. For a medium size system, testing effort can exceed translation cost by a factor of five to ten.
High translation accuracy and predictable runtime behavior are more important than small differences in per-line pricing. Any change in libraries, generated code, or runtime behavior increases test cycles and project risk.
SoftwareMining's approach is tried and tested in many large modernization projects. One major financial organization validated the generated Java code with more than 2 billion transactions. The process is secure because no COBOL code or business data leaves the client site, and all work is carried out by the client's own staff or their chosen system integrator. This ensures full control, predictable outcomes, and a safe modernization path.
In short, modernization success is driven by confidence, not cost per line.
COBOL modernization costs vary based on the chosen approach. IBM mainframes carry high annual runtime and licensing charges. AWS Mainframe Modernization shifts cost to usage-based cloud billing. SoftwareMining uses a per-line pricing model with predictable support tiers. For a medium size system, the overall cost profile differs across these options, especially when long-term testing and platform dependency are included.
SoftwareMining uses a transparent per-line pricing model. The total modernization cost depends on the size of the application, the number of COBOL lines of code, and the level of support required. This makes budgeting straightforward for medium and large systems.
The generated Java code is portable and runs on any Java-compliant platform. The application relies only on standard Java and a small, stable set of SoftwareMining runtime libraries that are delivered with the project. No source code or business data leaves the client environment during translation.
Annual ASM support provides updates and maintenance for the translation tool and runtime libraries without introducing usage-based runtime licensing or cloud dependency. This deterministic process reduces regression testing effort and avoids the vendor lock-in common in cloud-managed modernization solutions.
SoftwareMining generates predictable and consistent Java code, avoiding the variability found in automated or AI-driven tools. This greatly reduces regression testing effort, which is the main cost in most modernization projects.
The result is a portable application that runs on any Java platform with a small, reliable library set, giving organizations freedom from cloud or vendor lock-in and better long-term cost control.
For a medium size system, IBM mainframe runtime can reach the high six to low seven figure range per year. AWS Mainframe Modernization often lowers on-premise infrastructure costs, but annual cloud runtime and storage usually fall into the mid six figure range depending on workload and usage.
AWS Mainframe Modernization also introduces platform dependency. Migrated applications rely on AWS-native components such as the managed mainframe-compatible runtime, IAM security model, CloudFormation infrastructure, and AWS data and storage services. These features simplify deployment but tightly couple the system to the AWS ecosystem.
The main lock-in factors include:
In practice, moving an AWS-modernized system to another cloud or back on-premise can require major redesign and retesting. Organizations should include these long-term factors when evaluating total modernization cost and vendor strategy.
IBM watsonx Code Assistant supports partial modernization by generating Java around existing mainframe structures. Costs depend on AI model usage, cloud resources, and the volume of COBOL processed.
For a medium size system, organizations typically incur model consumption fees together with the ongoing cost of running a hybrid environment that still depends on mainframe components. This approach can reduce initial effort but is not a full mainframe exit.
The hybrid model also increases long-term testing and integration effort, since both the Java layer and the retained mainframe components must be validated together. In addition, reliance on IBM cloud services and AI runtime pipelines can lead to vendor lock-in compared to a deterministic COBOL to Java conversion that produces fully independent, portable code.
In many projects the largest cost is regression testing. A medium size system can include many connected business processes, and proving functional equivalence may require several test cycles that exceed translation cost.
