

Find out in this report how the two AI Software Development solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
Faster root cause identification helped me resolve incidents more consistently and reduced the amount of manual debugging effort.
I have seen debugging time decrease by around 20 to 30% because I can trace the COBOL programs and also inspect the variables.
I find it easy to use.
Every time I open a case, I get an immediate response.
BMC AMI DevX's technical support responds very well and takes all cases seriously.
I think the hybrid CI/CD integration with existing enterprise DevOps tools in BMC AMI DevX is very good.
I have used them sometimes, even recently, and found the feedback to be spot on our needs.
The features of MongoDB Atlas fall short, resulting in an average rating due to higher-expectation features still lacking in its offerings.
For premium support, I would rate the support of MongoDB Atlas a nine.
From my perspective, I haven't seen BMC AMI DevX struggle in terms of workloads where it needs to be scaled up or scaled down.
It can support multiple developers for COBOL applications as they debug different problems without changing the overall development process.
It has been scalable for our mainframe development and support needs, handling large COBOL programs and large workloads.
It's very much scalable, and I would rate scalability a nine.
MongoDB Atlas offers sharding as a scalability feature, although it does not perform as well as Oracle.
I would rate BMC AMI DevX as a stable solution that I have been using for years and find working fine.
BMC AMI DevX is very stable for a modern application processing huge workloads.
It has been reliable for COBOL debugging, code analysis, and troubleshooting production incidents.
When it comes to OLTP transactions, its performance declines.
The stability of the product is very high.
Being able to step through the COBOL program, set breakpoints, and monitor variable values gives me a much clearer picture of what is happening during execution.
I have to put my cursor on the field and tap it to bring focus there, or use the tab key multiple times to get to a field on the screen.
To improve BMC AMI DevX, consideration should be given to cloud-style provisioning and development models, as well as integration of more AI capabilities.
Enhancing capabilities for data pipelines and visualization dashboards.
MongoDB Atlas should support containerization.
The UI is good, although I have checked one aspect in MongoDB Atlas: when we make transactions, they do not process in real-time and require a refresh.
For our service, it was around 300 to 600 euros per month, which was acceptable for our customers.
The price of MongoDB Atlas is reasonable, which is why many organizations, including mine, are opting for it.
The CI/CD offering allows integration of quality checks and unit test processes into the pipeline, which improves compliance and enhances productivity, enabling developers to focus on development while the pipeline automates integration.
BMC AMI DevX's tools have affected my developers' productivity and efficiency by helping with the speed.
BMC AMI DevX positively impacts my organization with its modern VS Code and Eclipse development environment, integrated debugging, AI-assisted code understanding, automated CI/CD pipelines, and end-to-end mainframe DevOps workflow.
I find MongoDB Atlas highly scalable and easy to use, with very good support.
It is particularly useful for unstructured and semi-structured data because of its performance in these areas.
The most valuable features of MongoDB Atlas in handling large data volumes include collection size and its NoSQL database capabilities.
| Product | Mindshare (%) |
|---|---|
| MongoDB Atlas | 0.6% |
| BMC AMI DevX | 0.2% |
| Other | 99.2% |


| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 1 |
| Large Enterprise | 24 |
| Company Size | Count |
|---|---|
| Small Business | 24 |
| Midsize Enterprise | 12 |
| Large Enterprise | 23 |
BMC AMI DevX is a mainframe DevOps platform for IBM Z environments that helps development and platform engineering teams increase release velocity, reduce change risk, and build a sustainable mainframe developer workforce.
Whether the priority is attracting the next generation of mainframe talent, safely evolving decades of business-critical code, accelerating release velocity, or demonstrating development ROI to leadership — BMC AMI DevX is designed to address all on a single platform. Teams can connect existing tools and adopt capabilities incrementally using an open-borders integration approach.
A 2025 Forrester Total Economic Impact study found that customers using BMC AMI DevX onboarded developers 50% faster, completed code changes 33% faster, increased release frequency by 50%, and reduced change failure rate by 33%.
Key capabilities:
MongoDB Atlas stands out with its schemaless architecture, scalability, and user-friendly design. It simplifies data management with automatic scaling and seamless integration, providing dynamic solutions for diverse industries.
MongoDB Atlas offers a cloud-based platform valued for its seamless integration capabilities and high-performance data visualization. It features advanced security options such as encryption and role-based access control alongside flexible data storage and efficient indexing. Users benefit from its robust API support and the ability to manage the platform without an extensive setup process. Feedback suggests improvements are needed in usability, query performance, security options, and third-party tool compatibility. While pricing and support services could be more economical, there is a demand for enhanced real-time monitoring and comprehensive dashboards, as well as advanced containerization and scalability options supporting complex database structures.
What are the key features of MongoDB Atlas?
What benefits should you consider in a solution like MongoDB Atlas?
In healthcare and finance, MongoDB Atlas manages payment transactions and facilitates real-time analytics, powering SaaS solutions and storing large volumes of user data. It enhances scalability, performance, and security for cloud hosting, IoT integrations, and Node.js environments, widely favored for its flexibility and capability to support microservices.
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