Sold by: BMC Software
Deployed on AWS
Control-M SaaS is an application workflow orchestration platform that integrates, automates and orchestrates complex data and application workflows, leveraging AI capabilities across highly heterogeneous technology environments.
4.4
Overview
Fully Managed Enterprise AI Workflow Orchestration for AWS
Run mission-critical application, AI, and data workflows without managing infrastructure. Faster delivery, consistent governance, and scalable automation, powered by AI.
The solution integrates with Amazon Bedrock and leverages AWS GenAI services to create AI agents orchestrated by Control-M.
Control-M SaaS delivers:
- Fully managed enterprise AI orchestration, no infrastructure or upgrades to handle
- Centralized control across application workflows, file transfers, and data pipelines that keep workflows running on time
- Proven reliability, visibility, and governance for hybrid and multicloud environments
- Natively integrates with AWS services (S3, Bedrock, Snowflake, etc.) and hundreds of other enterprise systems
- Orchestrates AI agents in event-driven workflows
- Modern AI assistant (Jett) and agentic AI capabilities to create workflows
Start now by purchasing directly through AWS Marketplace.
All the power of Control-M; delivered as SaaS.
Highlights
- Simplifies workflows across hybrid and multi-cloud environments
- Deliver data-driven outcomes faster by managing production data pipeline workflows in a scalable way
- In-depth workflow observability with intelligent predictive analytics and reports
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Dimension | Description | Cost/12 months |
|---|---|---|
Units | One unit of Helix Control-M | $10,000.00 |
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BMC Does not provide refunds
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
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Support
Vendor support
BMC provides documentation and general support at our BMC DOCs site. We also offer direct support plans and support from BMC Partners. For more information please visit
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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By BMC Software
By BMC Software Distribution B.V.
By Workato, Inc.
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Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
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Positive reviews
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Negative reviews
AI generated from product descriptions
AI-Powered Workflow Orchestration
Orchestrates AI agents in event-driven workflows and integrates with Amazon Bedrock and AWS GenAI services to create AI agents within orchestrated workflows.
Multi-Cloud and Hybrid Environment Support
Provides centralized control and governance across application workflows, file transfers, and data pipelines in hybrid and multicloud environments.
Native AWS Service Integration
Natively integrates with AWS services including S3, Bedrock, Snowflake, and hundreds of other enterprise systems.
Workflow Observability and Predictive Analytics
Delivers in-depth workflow observability with intelligent predictive analytics and reporting capabilities for production data pipeline workflows.
AI-Assisted Workflow Creation
Includes modern AI assistant (Jett) and agentic AI capabilities to automate workflow creation and management.
Workflow Orchestration
Orchestrates application workflows across on-premises, public, private and hybrid cloud environments
Multi-Technology Integration
Integrates file transfers, applications and data sources through a rich library of plug-ins
Workflow Observability
Provides in-depth workflow observability with intelligent predictive analytics and reports
Data Pipeline Management
Manages production data pipeline workflows in a scalable manner
Unified Workflow Management
Delivers a single unified view for orchestrating all workflows across heterogeneous technology environments
Low-Code/No-Code Development
Platform enables building automation workflows and AI agents without requiring code writing, supporting rapid development and modification of business processes.
AI Agent Orchestration
Supports creation and management of intelligent AI agents (Genies) that understand intent, adapt to business processes, and collaborate with humans and other agents for end-to-end automation.
Event-Driven Workflow Automation
Enables reactive AI orchestrations with event-driven workflows for near real-time decision making and optional human oversight for critical processes.
Cloud-Native Auto-Scaling
Provides cloud-native execution with automatic scaling capabilities for high-demand AI workflows that continuously learn and adjust to support business growth.
Enterprise Integration Capabilities
Connects multiple cloud and on-premises applications including Amazon S3, Amazon SQS, Amazon SNS, Amazon RDS, Amazon Redshift, Amazon Lambda, and SaaS applications with enterprise-grade governance and security controls.
Standard contract
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Customer reviews
Hemanthreddy Vakiti
Automated scheduling has streamlined our data pipelines and improved cross-platform workflows
Reviewed on Mar 29, 2026
Review provided by PeerSpot
What is our primary use case?
I am currently working as a Data Engineer at Cognizant. I have been using Control-M for the past eight months since I joined Cognizant as a Data Engineer. As a Data Engineer, my job is to monitor jobs and maintain pipelines, and Control-M is a scheduler tool which we use to schedule jobs by linking the jobs as predecessors and successors so that the flow of the data pipelines continues without human interference.
The daily important task which we are monitoring is the SaleRPT report, which gives business users the sales that happened the previous day in a restaurant at our project in Cognizant. The jobs are connected in such a way that starting, there are replication jobs, and then they are connected to SQL Server to transform the data and load it into Oracle SQL. From there, again, the data is loaded into our data warehouse tables, and the final target tables are Essbase . So this total flow has around 17 to 18 jobs which are scheduled to run twice a day when we get EOD clearance for each site. So these are the latest tasks for which I used Control-M to schedule jobs in a sequential manner.
In our legacy system, there are some Informatica jobs and some SnapLogic jobs. For example, there are three sets of jobs which are from Informatica, and the next successor jobs are from SnapLogic . Control-M allows us to link these Informatica jobs to SnapLogic. If the Informatica job is completed, it would automatically trigger the SnapLogic pipeline. So it allows the usage of multiple tools. For DataOps and DevOps, it is quite important to use Control-M, as it is a scheduler which schedules multiple jobs based on our requirement. We can easily change the schedule for a particular day if we have a lesser number of data. And if there is any data miss, we can also easily reprocess using Control-M by putting a few jobs on hold and running the jobs manually. So I think it is quite extensively important to use Control-M for a Data Engineer at any level.
There are multiple teams which are using Control-M. I think there are nearly 80 to 90 employees who are using Control-M tool in my organization in my current project at Cognizant. Mostly, 60 to 70 percent of them are Data Engineers. Some are from the BI ETL, Business Intelligence ETL team, and some are from the DevOps team, and some are part of the development team also. And some are part of the Aloha Insight team. These are the teams which I know which are currently using Control-M.
What is most valuable?
I have been using Control-M to monitor and maintain pipelines. It helps us schedule jobs by linking them as predecessors and successors, ensuring the continuous flow of data without human interference. Control-M is the most used tool in my current project and is essential for job scheduling and checking job failures. Its easy interface makes it beginner-friendly.
Control-M's ability to link jobs from different tools such as SnapLogic, Informatica, and GCP DAGs enhances its functionality. The scheduler, ad hoc runs, and job linking features are particularly useful. It allows job connections to various tools and notifies us via email of any job failure, providing logs for quick rectification.
It can save us significant time, reducing errors and the time taken to rectify them. Automatic failure notifications enable rapid response, facilitating efficient job management. Control-M enables development on various platforms, which is essential for DataOps and DevOps operations.
Its user-friendly nature allows quick learning and management of tasks, with significant time savings compared to manual processes. We now receive automated failure notifications, which streamline error rectification and job reruns. Control-M's integration with Informatica and SnapLogic further exemplifies its efficiency.
What needs improvement?
One thing I find challenging is if a job is executing and we put it on hold, then if a job is an Informatica or SnapLogic job and we put it on hold, the corresponding pipeline in Informatica or SnapLogic would still be executing. We need to again go to that tool and kill the job. Rather, it would be easier if we kill the job in Control-M and it would automatically be killed in Informatica or SnapLogic.
In some cases, some jobs go into a waiting state. So again, we need to change the Control-M settings for that particular job manually to transform it into the normal flow. These are the two things that if they are changed, Control-M would be an even better tool.
For how long have I used the solution?
I have been using Control-M for the past eight months since I joined Cognizant as a Data Engineer.
What do I think about the stability of the solution?
We have never experienced any licensing or any security issues from Control-M. My manager and the other members of my upper hierarchy manage the pricing. Since I have been using Control-M for the past almost one year, I have never experienced any security or software issues in it.
What do I think about the scalability of the solution?
Control-M is easily scalable. I would rate it a nine out of ten when it comes to scalability of Control-M.
How are customer service and support?
I have not used customer support until now, as the monitoring and the management of Control-M is done by another team. However, the other team which currently manages Control-M has helped us a lot.
Which solution did I use previously and why did I switch?
When I was deployed into this project, Control-M was already in use, so I have not chosen or compared Control-M with other tools. Since I have been using it, I have not experienced any flaws or any issues.
What about the implementation team?
For development, maintenance, and changing, I think around four to five people are enough for monitoring. For development, we need quite a lot of them. Once it is developed, only three to four people can easily manage Control-M.
What other advice do I have?
I would recommend Control-M to most people. When it comes to metrics, I am not sure on how much the tool has saved us, but I am quite sure that it saved us a lot of time.
For scheduling, Control-M is the first tool which I have used. Along with Control-M, I am also using DAG monitoring, which is already enabled in GCP, which is almost similar to a scheduler.
We can easily depend on it to schedule the jobs and monitor them. I am already using it quite much for my daily tasks for my project. I am satisfied with the way I am using it and the features it is allowing me.
One thing is how easy it is to use. Anyone, if they open Control-M and look at the jobs, they can easily know how to run a job, how to kill a job, how to put it on hold, how to check the logs, when it started, when it ended, whether it is running fine, or if there are any anomalies in the job. So I would recommend it. I advise them that it is a good tool. I would rate this product an eight out of ten.
Tiago P.
Powerful Automation with Room for UI Improvement
Reviewed on Mar 25, 2026
Review provided by G2
What do you like best about the product?
I use Control-M to orchestrate batch jobs, mostly for files. It automates processes that would otherwise be manual, freeing up developer time and costs. I like its JaC approach since writing my jobs programmatically is much more advantageous compared to normal GUI-based tools. I also appreciate its vast network of integrations, which allows me to connect to many sources. Additionally, I connect Control-M with ServiceNow, Jira, and GitHub Actions.
What do you dislike about the product?
The user interface is the biggest. It’s outdated, frankly. Also, the learning curve is a bit steep for new people. Not easy at all. Setting up took a while, and many attempts.
What problems is the product solving and how is that benefiting you?
I use Control-M to orchestrate batch jobs, automating manual processes to free up developer time and reduce costs.
Ambedkar Vardhanapu
Automation has improved daily batch control and consistently ensures banking SLAs are met
Reviewed on Mar 19, 2026
Review provided by PeerSpot
What is our primary use case?
My main use case for Control-M is to control the batch for the day by scheduling the jobs, ensuring that all jobs run on time, and verifying that all conditions are met. Sometimes I force complete the jobs or rerun failed jobs by fixing the JCLs, and I ensure all batches are completed on time and all SLAs are met.
A specific example of a batch process I manage with Control-M is a weekly job which runs from Monday to Friday on all working days, and I ensure the job is completed on time. I also verify that if any files are pending to process which that job needs, the file is available so that the job can run once the file is available. Such scenarios are common in my work.
Regarding my main use case, I work on automation and ensure that there are no human errors. Everything we use is up to date, and we make sure to follow the SOPs perfectly.
What is most valuable?
Control-M offers several best features, including its user-friendliness. Compared to TWS and CA 7, Control-M is a tool wherein if you get training for 10 to 12 days, you can learn almost everything, and it is very good and simple to use.
What makes Control-M user-friendly for me is that we connect through the client interface, which is easy to log in to, and there is no downtime for it. Control-M is only recycled weekly. It is straightforward to define and monitor the jobs and to get insights from the zoom panel. The coloring shows us in yellow if a job is executing, red if it has failed, and other colors for different conditions, making it simple.
Control-M has positively impacted my organization, especially when new team members join as their first assignment. It is a tool we can explain quickly, giving them a few sessions to work in production or development environments faster compared to other tools like CA 7 or TWS.
In our organization, we work for a banking client where we handle 10,000 jobs running on Control-M daily. Managing those jobs would be difficult with other tools due to visibility issues. With Control-M, it is easier to manage workloads and handle abends, and the chances of missing things are significantly less compared to command-based tools like CA 7.
What needs improvement?
Control-M can be improved in several areas. Last week when creating a job, I found that the option for global conditions could be more streamlined, as well as the in and out conditions, which are a bit complicated. Integrating more AI options, such as automatically marking jobs that are known to fail as complete, would be beneficial.
For how long have I used the solution?
I have been using Control-M for the last 16 years.
What do I think about the stability of the solution?
Control-M is 100% stable.
What do I think about the scalability of the solution?
Regarding scalability, I would say it is good and there are always possibilities for scalability.
How are customer service and support?
Customer support from BMC, who owns Control-M, is excellent. They provide good support for critical issues, and I would rate it 99% out of 100.
Which solution did I use previously and why did I switch?
I have experience working on CA 7 and TWS. While CA 7 is a good tool, Control-M is better due to its simplicity and less complicated nature.
How was the initial setup?
To deploy Control-M, I would say two resources would be sufficient for proper installation and defining architecture, security levels, and access control.
What about the implementation team?
In our team, approximately 24 users utilize Control-M, with 15 members working 24/7 for batch operations and nine members focusing on scheduling tasks during business hours.
What was our ROI?
Regarding return on investment, training a resource on Control-M allows them to handle two or three clients at the same time, thus saving costs for the company and making it easier to train.
What's my experience with pricing, setup cost, and licensing?
Those things are managed by the sales team. I do not have much visibility regarding pricing, setup cost, or licensing.
Which other solutions did I evaluate?
We evaluated Jobtrac, CA 7, and TWS before making our decision.
What other advice do I have?
The biggest lesson I have learned from using Control-M is time management, reliability, and the tool's availability, which makes our work easier.
I advise that if you have banking or insurance requirements or operate in a small industry, you can definitely consider Control-M as your first option.
I provided this review with an overall rating of 10 out of 10.
Computer & Network Security
Complex Setup Holds Back an Otherwise Strong Workflow Scheduler
Reviewed on Mar 18, 2026
Review provided by G2
What do you like best about the product?
Centralized scheduling and monitoring of workflows makes it easier to manage complex batch jobs. The interface provides good visibility into job status and dependencies, which helps reduce manual effort and improves reliability.
What do you dislike about the product?
The setup and configuration can be complex, especially for new users.
What problems is the product solving and how is that benefiting you?
it's soling monitoring of workflows and this is how it benefits me
Paulo Ramada
Orchestration has transformed complex batch invoicing and now simplifies cross-platform workflows
Reviewed on Mar 13, 2026
Review from a verified AWS customer
What is our primary use case?
I lead a team of Control-M schedulers and operators, and I also do some scheduling myself. A specific example of a task or workflow I manage with Control-M is that I have re-engineered a monolithic script. The process I re-engineered was designed for printing invoices, specifically the invoices of EDP clients, which amounts to about eight million invoices per month.
To handle that scale with Control-M, I made changes by decomposing the monolithic script, which was made in shell scripting, into Control-M jobs, getting the complete workflow, a PDF, and transforming it into a Control-M workload. I do a lot of transformation from monolithic scripts or jobs that can be transformed into workloads within Control-M.
What is most valuable?
The best features Control-M offers include cross-platform dependency management, which is interesting because a job on the mainframe depends on a file arriving from a Unix system that, in turn, depends on a Windows process completing, and Control-M handles that heterogeneous dependency chain natively.
A time when this feature really made a difference for my team was when we had several workloads that are dependent on each other, using different platforms, and that interconnection between those platforms is really relevant to the whole process. There are more features that add value to Control-M, such as the calendar and condition system, which is really powerful to schedule almost to perfection many workloads that are critical for the business, whether in energy, insurance, banking, etc., because it maintains the logic.
Using the conditions allows me to create the re-engineering process that I have mentioned, which depends not only on the conditions but allows everything to run smoothly and on time. Tasks that in the original monolithic script would take about two hours now take at least fifty percent less time because it is more efficiently designed. The time savings were enabled mostly by parallelization, but not only that; I can adjust several aspects.
Control-M has positively impacted my organization because if some condition fails or if a calendar is incorrectly defined, a simple error in a condition can stop a critical workload, stop invoicing, and stop files that should go to the banking system.
What needs improvement?
Control-M can be improved with better integration with modern DevOps toolchains, as while it has made strides with APIs and the automation API, integration with tools such as JIRA and ServiceNow could be more seamless out of the box.
There is also a knowledge barrier that BMC should be aware of; Control-M has a steep learning curve for deep operational mastery, where basic administration is fairly accessible, but truly understanding the platform takes months to years for a new person, and BMC could invest more in advanced training and certification paths beyond the basics.
For how long have I used the solution?
I have been using Control-M for more than twenty years, since around 1996.
What do I think about the stability of the solution?
Control-M is stable in my experience. I have worked with Control-M environments processing tens of thousands of jobs, and currently, we have around six thousand jobs in the energy company.
What do I think about the scalability of the solution?
Control-M is used quite extensively; we execute around six thousand jobs a day, serving around seventy to eighty applications, and it is always growing, also serving many DevOps teams.
How are customer service and support?
BMC support is generally competent for standard issues.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
Before choosing Control-M, I always worked with it and know alternatives such as TWS, Autosys, and other platforms similar to Control-M, but I have never worked with them.
What was our ROI?
The ROI of Control-M in critical infrastructure is less about percentage savings and more about what does not fail, such as when a national payment system opens every morning on time, or when millions of transactions are processed without a missed dependency.
What's my experience with pricing, setup cost, and licensing?
Control-M has premium pricing, which is justified for enterprise-scale operations, as we are paying for a platform with decades of maturity, proven reliability, and the capacity to handle complex orchestration scenarios that simpler tools cannot manage.
What other advice do I have?
I have always worked with Control-M, first on banking systems and then on energy systems, and though I worked with other systems, Control-M was always present. We have many users in many different roles; there are maybe four or five administration roles along with operation roles.
The biggest lesson I have learned from using Control-M is that it makes your life easier in dealing with batch processing, whether on mainframe or distributed servers, allowing you to define everything the way you want. I advise others looking into using Control-M to invest in people, not just the tool, emphasizing that a well-configured Control-M environment with experienced operators is essential for reliability.
Integrating Control-M with technologies for our data ops and DevOps processes can be difficult as technologies change. I would rate this review nine out of ten overall.
Which deployment model are you using for this solution?
Public Cloud