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    Control-M SaaS Starter Pack

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    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.
    4.3

    Overview

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    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.

    Learn more about Control-M  

    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

    Details

    Delivery method

    Deployed on AWS
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    Buyer guide

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    Buyer guide

    Financing for AWS Marketplace purchases

    AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
    Financing for AWS Marketplace purchases

    Pricing

    Control-M SaaS Starter Pack

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    Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.

    12-month contract (1)

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    Dimension
    Description
    Cost/12 months
    Starter Pack (SaaS)
    Control-M SaaS Start with 500 Executions (Base package)
    $29,000.00

    Vendor refund policy

    BMC does not provide any refunds

    Custom pricing options

    Request a private offer to receive a custom quote.

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    Vendor terms and conditions

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    Usage information

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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.

    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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    Customer reviews

    Ratings and reviews

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    4.3
    311 ratings
    5 star
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    57%
    41%
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    36 AWS reviews
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    275 external reviews
    External reviews are from G2  and PeerSpot .
    Chaitra Anurag

    Automation has reduced manual intervention and supports reliable, seamless job scheduling

    Reviewed on Sep 17, 2026
    Review provided by PeerSpot

    What is our primary use case?

    Control-M is a reliable service provider, specifically for workload automation and job scheduling. In terms of monitoring and dependency management capabilities, it would be more viable and definitely help in reducing manual intervention.

    What is most valuable?

    My favorite thing about Control-M is the automation of workloads.

    In terms of what I could see improved in Control-M, it involves the integration capabilities with other software. Currently, the specificities are somewhat limited, and capturing and configuring the workload can be made much easier and seamless. I wouldn't say that it needs to be changed because whatever is built is constructed in such a manner for certain reasons. However, particularly for new users, if the configuration can be made simpler, that would be helpful.

    What needs improvement?

    Integration capabilities with other software could be enhanced. Currently, the specificities are somewhat limited, and capturing and configuring the workload can be made much easier and seamless. Whatever is built is constructed in such a manner for certain reasons. However, particularly for new users, if the configuration can be made simpler, that would be helpful.

    For how long have I used the solution?

    I have been working with Control-M overall, with BMC, for roughly 18 months, equivalent to 1.5 years.

    What do I think about the stability of the solution?

    In terms of stability, I have not seen any downtime with Control-M.

    What do I think about the scalability of the solution?

    Control-M is definitely scalable. It was seamless and easily scalable.

    How are customer service and support?

    I have not personally contacted their support, but I am aware that my team reached out one or two times in the past.

    My experience with Control-M support in terms of speed is that they were fast and reliable. They were able to understand the issue and fix it quickly.

    If I were to score the support on a scale from 1 to 10, with 10 being the highest, I would give them a nine or 10.

    Which solution did I use previously and why did I switch?

    If I were to pick between Control-M and other solutions, I would definitely go with BMC Control-M.

    How was the initial setup?

    The initial deployment of Control-M was easy, considering we went through a seamless training module that was provided to us. It was also comprehensive enough for us to understand, and from my technical background, it was much simpler.

    What about the implementation team?

    As for maintenance, it is done by BMC. If we raise a ticket, it is managed by them.

    What other advice do I have?

    My relationship with BMC is more transformative. I would rate this review a 9 out of 10.

    MohammedMukhtar

    Job scheduling has provided clear visibility into dependencies and efficient failure analysis

    Reviewed on Sep 17, 2026
    Review provided by PeerSpot

    What is our primary use case?

    I have been using Control-M in my career overall for quite some time. I joined this company about five years ago, but Control-M has been used there for way before, perhaps eight years, nine years, or more than that.

    What is most valuable?

    What I like the most about Control-M is that it is very reliable and works well for scheduling and even monitoring. The best thing I could say is the good visibility of jobs and their dependencies. When something fails, suppose when multiple jobs are affected, it would be useful to quickly identify the original failure and what was impacted because of it. Otherwise, it has very good visibility, scheduling jobs, and status is everything is good.

    What needs improvement?

    When something fails, as an improvement, it would be useful to have a clear explanation of what actually went wrong. The interface can sometimes feel a little busy for us. Finding the right information can take some time. It is not that we cannot find it, but it takes a few clicks. It is always helpful to have something very clear that quickly identifies what went wrong.

    For how long have I used the solution?

    Control-M has been used there for way before, I joined perhaps eight years, nine years, or more than that.

    What do I think about the stability of the solution?

    Regarding stability, there is no lagging and no issues with stability; it is pretty good.

    What do I think about the scalability of the solution?

    Regarding scalability, I can say ten out of ten because it gives very good visibility of all the jobs and stability. There is no crash or downtime. It runs pretty well.

    How are customer service and support?

    I have contacted the technical support or customer support of Control-M;. If we have any issues or need any help, we do contact them and raise tickets.

    Regarding the quality and the speed of the support, as of now, I can say that it is acceptable. The response time is quite good. When we need them to be on call to help us, we decide on time and they come online to assist us. So it is acceptable.

    Which solution did I use previously and why did I switch?

    I have never used any alternatives or something similar; we have been using Control-M for quite some time.

    How was the initial setup?

    Regarding how easy or difficult it was to learn how to use Control-M, we have been using both web client and fat client, and I feel that the fat client is easier than the web client. There are a lot of options in the web client. With the fat client, I get more visibility and a more user-friendly interface. In terms of easiness, since it was already deployed and the functionality was there, it was pretty easy with some training from my team. It was not so hard to get through Control-M.

    What about the implementation team?

    Control-M does require some maintenance on my end; we have periodic updates and patches. However, that is regular and that is needed to patch the vulnerabilities. Other than that, there is not much maintenance required.

    What's my experience with pricing, setup cost, and licensing?

    I am not familiar with the pricing;I think it is still in discussion with Control-M.

    Viju D.

    Reliable Workflow Automation with Strong Scheduling and Monitoring

    Reviewed on Sep 15, 2026
    Review provided by G2
    What do you like best about the product?
    What I like most about it is its ability to reliably automate and manage complex workflows. It offers strong scheduling, monitoring, and dependency management, which makes it easier to ensure jobs run on time and that issues are identified and resolved quickly.
    What do you dislike about the product?
    One thing I find challenging is that it can be complex to manage and troubleshoot, especially in environments with a large number of jobs and dependencies. The interface and configuration also take some time for new users to learn and get comfortable with. That said, its strong scheduling, monitoring, dependency management, and automation capabilities still make it very valuable for enterprise workloads.
    What problems is the product solving and how is that benefiting you?
    It helps us automate and manage complex batch workflows by scheduling jobs, handling dependencies, monitoring executions, and alerting us when failures occur. As a result, we spend less time on manual intervention and face a lower risk of missed jobs or tasks running in the wrong sequence. It also provides clearer visibility into the overall workflow, which helps us troubleshoot issues more quickly and improve operational efficiency. Overall, it saves time, reduces errors, and makes our job scheduling and production operations more reliable.
    Maalini K.

    Control-M Turns Hybrid Scheduling into a Deterministic, SLA-Smart Orchestration System

    Reviewed on Sep 11, 2026
    Review provided by G2
    What do you like best about the product?
    What sets Control-M apart is its ability to eliminate the "invisible critical path" failure across hybrid infrastructure. In complex environments, the primary risk is rarely a complete server outage; it is unmonitored downstream latency creep. Native platform schedulers—whether on AWS, Azure, or legacy mainframes—operate in operational silos. A fifteen-minute delay in an on-premises transactional batch job can silently starve downstream cloud analytics pipelines hours later.
    Control-M transforms these isolated tasks into a deterministic operational nervous system. By leveraging the Automation API, engineering teams can define orchestration as declarative code directly within standard CI/CD pipelines. This gives developers autonomous workflow ownership without sacrificing production governance, compliance auditability, or resource management. Furthermore, its Batch Impact Manager proactively recalculates critical path variance based on dynamic runtime history, identifying SLA drift hours before a breach occurs rather than firing reactive alerts after a job has already failed.
    What do you dislike about the product?
    The biggest hurdle with Control-M is that its architectural sophistication, granular governance rules, and sheer depth of enterprise orchestration power create a steep learning curve, requiring teams to fundamentally elevate their operational standards just to take full advantage of how capable the platform actually is.
    What problems is the product solving and how is that benefiting you?
    The core business challenge Control-M addresses is operational friction and systemic delivery risk across fragmented hybrid architectures. Enterprises routinely struggle with brittle data handoffs when mission-critical systems of record, on-premises legacy databases, and distributed cloud applications run on disconnected native schedulers. Without centralized visibility, teams inevitably face silent pipeline stalls, SLA breaches, and costly manual firefighting.
    Control-M mitigates this vulnerability by serving as a unified, deterministic orchestration backbone. The operational and commercial benefits are significant:

    Guaranteed Service Level Agreement integrity comes from real-time critical-path tracking that dynamically recalculates execution timelines based on historical variance. This helps prevent delays in time-sensitive transactional settlements, payroll runs, and regulatory reporting, instead of merely surfacing post-failure alerts.

    Radical cost reduction and operational efficiency follow from replacing fragile custom scripts and scheduled cron routines with native, event-based workflow dependencies. This reduces manual triage hours and frees engineering talent to focus on product velocity rather than maintaining low-level orchestration plumbing.

    Unified governance without sacrificing agile velocity is enabled by integrating workflow definitions into CI/CD pipelines as declarative code. This allows cross-functional developers to deploy workloads quickly while still maintaining rigorous compliance auditability, role-based controls, and end-to-end operational visibility across the broader data estate.
    krishna K.

    Control-M Makes Automation and Job Monitoring Effortless

    Reviewed on Sep 09, 2026
    Review provided by G2
    What do you like best about the product?
    What I like most about Control-M is its automation and monitoring capabilities. It makes it easy to manage job dependencies, track job status, and quickly identify failures without having to monitor everything manually.
    What do you dislike about the product?
    One area that could be improved is the user interface and troubleshooting experience. Sometimes it can take time to understand the root cause of a failed job, especially when there are multiple dependencies. Better error messages, simpler navigation, and more detailed failure explanations would make Control-M easier to use.
    What problems is the product solving and how is that benefiting you?
    Control-M helps us automate job scheduling, manage dependencies, and monitor data workflows instead of handling them manually. This saves time, reduces human errors, and helps us identify and resolve failed jobs faster, making our overall process more reliable.
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