Apache Airflow is an open source tool that can be used to programmatically author, schedule and monitor data pipelines using Python and SQL.
N/A
Azure DevOps
Score 8.1 out of 10
N/A
Azure DevOps (formerly VSTS, Microsoft Visual Studio Team System) is an agile development product that is an extension of the Microsoft Visual Studio architecture. Azure DevOps includes software development, collaboration, and reporting capabilities.
$2
per GB (first 2GB free)
Control-M
Score 9.3 out of 10
N/A
Control-M from BMC is a platform for integrating, automating, and orchestrating application and data workflows in production across complex hybrid technology ecosystems. It provides deep operational capabilities, delivering speed, scale, security, and governance.
$29,000
per year
Pricing
Apache Airflow
Azure DevOps
Control-M
Editions & Modules
No answers on this topic
Azure Artifacts
$2
per GB (first 2GB free)
Basic Plan
$6
per user per month (first 5 users free)
Azure Pipelines - Self-Hosted
$15
per extra parallel job (1 free parallel job with unlimited minutes)
Azure Pipelines - Microsoft Hosted
$40
per parallel job (1,800 minutes free with 1 free parallel job)
Azure DevOps required the least amount of up front knowledge to get a pipeline up and running. Because of the built in activities, when I initially started working with this tool I didn't have to know anything other than where my code was stored. The rest was easy enough to …
We need end to end automation, so using Control-M we can achieve this but by using Azure Automation it automates data pipelines across the cloud. Compared to Autosys, Control-M has more advanced and modern UI and simple job life cycle management. When compared with Apache …
It supports both on-prem and cloud environments. Easy to handle complex, multi-system workflows more efficiently. Helped reduce manual intervention, which has decreased errors and operational costs.
Control-M stands out in the workload automation space for its robust orchestration capabilities, especially in complex, hybrid IT environmentsActiveBatch: Known for its rich integrations and intuitive workflow designer,
ActiveBatch often scores higher in ease of use and …
We have been using Control-M for almost 20 years and our teams are already trained to use it. Other tools are not as robust and resilient as Control-M. Control-M's graphical interface is very easy to use.
We would still use Control-M as overall orchestrator to manage the workflows created in these other products. We do not consider them as a replacement for Control-M.
It is a very innovative and feature-rich solution and can be used to complete many diverse tasks and solve different issues, resulting in significant time savings and cost-effectiveness.
We looked at several other competitors to Control-M and had even gone back after having it installed and running for a while to make sure we were using the right tool. We always felt that Control-M had the right mix of feature and benefits to suit our needs. We never considered …
Airflow is well-suited for data engineering pipelines, creating scheduled workflows, and working with various data sources. You can implement almost any kind of DAG for any use case using the different operators or enforce your operator using the Python operator with ease. The MLOps feature of Airflow can be enhanced to match MLFlow-like features, making Airflow the go-to solution for all workloads, from data science to data engineering.
Azure DevOps works well when you’ve got larger delivery efforts with multiple teams and a lot of moving parts, and you need one place to plan work, track it properly, and see how everything links together. It’s especially useful when delivery and development are closely tied and you want backlog items, code and releases connected rather than spread across tools. Where it’s less of a fit is for small teams or simple pieces of work, as it can feel like more setup and process than you really need, and non-technical users often struggle with the interface. It also isn’t great if you want instant, easy programme-level views or a very visual planning experience without putting time into configuration.
Anytime you have a process that has to do multiple things, transfer data, interact with other systems, Control-M is critical. Not only does it provide the insight to what is going on, but it also lets you keep tight audit controls over access, reduces the need to spend large amounts of time tracking down issues, reduces the need to write custom "code" to do integrations with other systems and helps you better manage and track critical SLAs for workflows across the business.
Apache Airflow is one of the best Orchestration platforms and a go-to scheduler for teams building a data platform or pipelines.
Apache Airflow supports multiple operators, such as the Databricks, Spark, and Python operators. All of these provide us with functionality to implement any business logic.
Apache Airflow is highly scalable, and we can run a large number of DAGs with ease. It provided HA and replication for workers. Maintaining airflow deployments is very easy, even for smaller teams, and we also get lots of metrics for observability.
The good thing is that there are so many connectors available. Control-M provides lots of features, and we are using almost 60 to 70% of them. Control-M is providing us with so much capability to use during our daily problem-solving.
Most of the job creation is very simple and quick and worked as per expectations.
Testing and debugging are also very easy, and you can test multiple scenarios using temporary changes during job runs.
Log and output presentations are also very good, short and detailed.
To monitor specific job net, we can create viewpoint, which can be use on daily basis.
UI/Dashboard can be updated to be customisable, and jobs summary in groups of errors/failures/success, instead of each job, so that a summary of errors can be used as a starting point for reviewing them.
Navigation - It's a bit dated. Could do with more modern web navigation UX. i.e. sidebars navigation instead of browser back/forward.
Again core functional reorg in terms of UX. Navigation can be improved for core functions as well, instead of discovery.
I did mention it has good visibility in terms of linking, but sometimes items do get lost, so if there was a better way to manage that, that would be great.
The wiki is not the prettiest thing to look at, so it could have refinements there.
I haven't come across too many spots where I'm not happy with the product. Most of the shortfalls were in my knowledge of the product as opposed to the actual product. Currently we're having a little bit of an issue with the deployment of the software to the servers, but it's more of an "us" problem than a product problem. I can't really give any good examples of shortfalls of the product that I've found so far.
I don't think our organization will stray from using VSTS/TFS as we are now looking to upgrade to the 2012 version. Since our business is software development and we want to meet the requirements of CMMI to deliver consistent and high quality software, this SDLC management tool is here to stay. In addition, our company uses a lot of Microsoft products, such as Office 365, Asp.net, etc, and since VSTS/TFS has proved itself invaluable to our own processes and is within the Microsoft family of products, we will continue to use VSTS/TFS for a long, long time.
It is one of the best solutions on the market, in terms of innovation, reliability and stability. Control-M provides security when used by the largest companies in Mexico such as banks, department stores and logistics. It has proven to be able to integrate with new technologies on the market and provide almost 100% availability, thanks to its automatic FailOver scheme.
For its capability to connect with multicloud environments. Access Control management is something that we don't get in all the schedulers and orchestrators. But although it provides so many flexibility and options to due to python , some level of knowledge of python is needed to be able to build workflows.
It's a great help to get more information about new feature release and stay updated on what the dev team is working on. I like how easy it is to just login and read through the work items. Each work item has basic details: Title, Description, Assigned to, State, Area (what it belongs to), and iteration (when it’s worked on). See image above.They move through different states (New → Discovery → Ready for Prod → etc.).
User experience is meeting my expectations. We had a manual checklist, which Control-M Reports has now replaced, that helped us check the jobs without any issues. So, being fair with the work, the ratings should also be fair. More to come as the AI progresses; this will not only help motivate the Control-M Developers but also lead to the development of advanced technology.
Secondary Instances: Control-M supports the installation of a secondary instance of the entire Control-M environment, Control-M/EM, or Control-M/Server.Automatic & Manual Failover: In case of a failure on the primary host, Control-M can automatically failover to the secondary host if using Oracle or MSSQL databases. Manual failover is also an option, enabling a controlled switch during planned maintenance.Fallback: After resolving the issue on the primary host, you can easily fall back to it, or even designate the secondary host as the new primary. Database Replication: For high availability, Control-M leverages database replication from the primary site to a disaster recovery site. While replication is essential, its implementation and maintenance are the user's responsibility.
good page load times, efficient report completion, and minimal impact on integrated systems. Specifically, the well-designed GUI contributes to a positive user experience, and the platform's ability to automate various stages of the workflow, including Big Data processes, is highlighted as a key strength. Fast Page Loads: Control-M is reported to have a responsive user interface with fast page load times, allowing users to quickly navigate and manage their workflows
When we've had issues, both Microsoft support and the user community have been very responsive. DevOps has an active developer community and frankly, you can find most of your questions already asked and answered there. Microsoft also does a better job than most software vendors I've worked with creating detailed and frequently updated documentation.
Support is generally excellent. Getting lower priority ones resolved can take a while, but it's rare for something to have to be dumped in the "unfixable" bin. If you end up speaking to Houston or Tel Aviv, then you know you've got a "live one".
Very knowledgeable instructors provide a hands-on, collaborative learning experience and can interact directly with instructors to develop our Control-M skills. This format allows for immediate feedback, in-depth discussions, and tailored guidance, leading to a deeper understanding of Control-M concepts and practical application. Face-to-face interaction fosters higher engagement and a more dynamic learning environment.
Simple and easy to use web based, well paced. Available any time. All online courses are simple and easy to access and use. Very practical everyday use scenarios and solutions. Incorporates software simulations, learning games, and built-in assessments to enhance comprehension and engagement. Online subscriptions are regularly updated with the latest product information, ensuring users have access to the most current knowledge.
As HA we have depend on the external DB, why don't we have HA feasibility with embedded DB. As with external DB, there are performance issues and fine tuning the DB. As if its embedded DB, Control-M it self take care of the functionality.
Multiple DAGs can be orchestrated simultaneously at varying times, and runs can be reproduced or replicated with relative ease. Overall, utilizing Apache Airflow is easier to use than other solutions now on the market. It is simple to integrate in Apache Airflow, and the workflow can be monitored and scheduling can be done quickly using Apache Airflow. We advocate using this tool for automating the data pipeline or process.
Microsoft Planner is used by project managers and IT service managers across our organization for task tracking and running their team meetings. Azure DevOps works better than Planner for software development teams but might possibly be too complex for non-software teams or more business-focused projects. We also use ServiceNow for IT service management and this tool provides better analysis and tracking of IT incidents, as Azure DevOps is more suited to development and project work for dev teams.
Control-M: Known for its comprehensive workload automation capabilities, handling complex job scheduling, dependency management, and IT process automation. TWS: Traditionally strong in Batch processing and job scheduling, focusing on high-performance computing environments. TIDEL: Offers a combination of workload automation and IT process management, often used in mainframe environments.AutoSys: Provides job scheduling and workflow management with a reputation for scalability and performance.
While Control-M offers flexibility with usage-based and subscription-based pricing, some users might prefer more predictable, upfront costs, especially for large-scale deployments. A potential area for improvement could be offering more options for fixed-term contracts with predictable pricing based on factors like the number of agents or jobs, providing a clearer budget for long-term planning
awesome product.Control-M delivers advanced operational capabilities easily consumed by Dev, Ops, data teams, and lines of business.Control-M Workflow InsightsApplication and data workflow observability: Increased confidence that SLAs are being met for Control-M users and IT leadersComprehensive control and management capabilities: Enhanced dashboards and reporting with constant telemetry and intelligent analysis on executing workflowsSelf-service visibility: In-depth reporting to help teams work autonomously
Strengths: The vendor provided strong post-sales support, timely issue resolution, and effective onboarding. Their technical team was knowledgeable and responsive, ensuring smooth integration and minimal disruption. Training resources and documentation were comprehensive. Areas for Improvement: While overall service was excellent, occasional delays in advanced customization or escalations slightly impacted timelines. More proactive optimization suggestions could further enhance value.
Impact Depends on number of workflows. If there are lot of workflows then it has a better usecase as the implementation is justified as it needs resources , dedicated VMs, Database that has a cost
We have saved a ton of time not calculating metrics by hand.
We no longer spend time writing out cards during planning, it goes straight to the board.
We no longer track separate documents to track overall department goals. We were able to create customized icons at the department level that lets us track each team's progress against our dept goals.
Since centralizing all our workflows in Control-M, we've cut end to end processing time by nearly 30%
Before Control-M we were babysitting scripts, manually rerunning failed jobs, and chasing ghost errors. With automated recovery, smart notifications, and fewer failures slipping through the cracks, we have saved 3 hours a day across teams
Our workflows success rate sits at 99.95% and when things do fail, they are pinpointed immediately
