AutoSys Workload Automation vs. Tidal by Redwood

In Informatica or Spark ETL jobs loading data into a Data Warehouse using AutoSys Workload Automation triggers ETL pipelines, monitors completion of jobs and also triggers the power bi report refresh. AutoSys Workload Automation can schedule jobs based on file arrival, and provide alerts if any data loads get failed. A small data team managing greater than 100 jobs. Buying and maintaining AutoSys Workload Automation is overkill in terms of cost, complexity and maintenance does not justify the value

Incentivized

On coming to well suited experience while error handling and effortless recovery processes are crucial, Tidal performs exceptionally well. It can identify and fix automated issues, reducing downtime and interruptions. A smaller automation solution may be more cost-effective if a business primarily utilizes a single platform or uses a small number of applications that do not require complex integration.

Incentivized

• AutoSys Workload Automation is our scheduler that automates and monitors workflows across all our system reducing manual runs
• Applications which run over multiples systems(cloud, on premise) are coordinated using AutoSys Workload Automation
• AutoSys Workload Automation clustering or failover ensures that workloads continue without any issue.
• AutoSys Workload Automation maintains execution logs and job history, which helps in compliance, audit trails, and root-cause analysis.

Incentivized

• Tidal Automation allows us to automate and schedule/ perform various tasks in a easy and effective manner. It is highly interactive and effective allowing nearly 4k -5k jobs to run a day.
• Tidal is designed to be easily shareable and collaborative allowing multiple users to work at a particular time making work effective.
• Tidal allows us to ensure that every event which is triggered is exactly when it's supposed to be regardless of other activities which are going as well.
• It is user-friendly to generate the reports required of a particular object and allows us to test the codes perfectly well before executing in live environment.

• In AutoSys Workload Automation, Workflow and job dependencies are shown in a static way, which makes user difficult to visualize more complex job chains or debug failures in a graphical view.
• Latest schedulers (like Control-M, Airflow) allow more easy workflow design makes user to understand it better, but AutoSys Workload Automation relies heavily on JIL scripts and text-based job definitions.
• AutoSys Workload Automation interface is very slow when searching or filtering over thousand of jobs

Incentivized

• Still a bit slow when navigating. If you close a job you have to wait a few seconds to open another one. Even when you made no changes.
• When viewing a job and make no changes, the "ok" button changes the last modified date as if you made a change. No big deal, but wastes time when troubleshooting a problem and looking into what jobs were changed last.
• You can see the parameters column in the "job activity", but not in "Job definitions".
• Can't search the parameters field in the filter.
• Changing a variable name does not change it on the job. It still works because Tidal Automation uses the ID number. It just causes confusion when you see a variable on a job and can't find the variable under "Variables". On top of that, Tidal Automation does not show the ID column under "Variables" making it even more difficult to find the variable.

We are on the fence. The increased pricing for renewals is staggering. With new automation options like Microsoft's Power Automate and Event Driven Ansible on the field, there are other options now available.

AutoSys Workload Automation is a place to schedule, monitor, and manage thousands of jobs. Time, file arrival, dependencies are much very flexible. Once jobs are set up they run consistently with minimal intervention. AutoSys Workload Automation is powerful but very complex o understand. Mainly for beginners the interface is not user friendly. AutoSys Workload Automation is very useful in terms of job scheduling and automation. AutoSys Workload Automation is also useful for strong logging and reporting purpose. AutoSys Workload Automation has reduced a lot of human efforts and manual processing.

Incentivized

Having provided consulting services for years on Tidal by Redwood, I recommend going with a solutions partner or consultant to deploy it. I believe there are sizing and tuning guidelines that should be followed for environments of scale. I believe they are not critical when first lighting up the product, but if you are not aware of them you will encounter performance degradation after a few thousand job objects are added.

In AutoSys Workload Automation, strong legacy presence, proven reliability, slightly simpler for basic scheduling if user already have in-house AutoSys Workload Automation expertise. so we already had investments in AutoSys Workload Automation, trained team, and large numbers of jobs running thus making AutoSys Workload Automation more cost-effective to continue rather than migrate to use AutoSys Workload Automation over Control-M. All our workloads are heavily batch-driven (SAP, ETL) real-time pipelines. AutoSys Workload Automation provides the robustness and enterprise support that Airflow lacks without heavy internal engineering overhead.

Incentivized

1. Tidal is good at processing large volume pf data and is cost effective. 2. Tidal can automate the scheduling of production objects, ensure that materials are delivered on time 3. Tidal Process large volumes of data which cannot be done everyday by running codes/scripts manually which does it with ease when required.

Incentivized

• Critical job process consistently complete on time without delays
• Significant reduction in team effort due to this resources for available for higher-value tasks. Human intervention is reduced due to this incident costs are also reduced.
• Faster incident resolution, improved productivity, and lower downtime.

Incentivized

• Better decision-making and more process visibility are achieved through reporting and monitoring.
• Lowered time frames and streamlined administration of the workflow.
• Improved cost and resource allocation, especially in cloud contexts.
• A decrease in manual errors and related expenditures.
• Unusual problems that could occur during automation.
• Possible difficulties shifting to a new automation tool.
• The expense of beginning implementation and training.

Incentivized