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Top 7+ Workload Automation Tools of 2024: Vendor Benchmark

Multi-cloud environments are anticipated to increase by ~67%, and hybrid cloud environments by ~72% (Figure 1). With this increase in complexity, ~73% of top IT executives report that managing multi-cloud environments is challenging. 1 Workload automation tools (WLA) can assist in managing data utilization in multi and hybrid cloud environments thanks to capabilities such as managed file transfers, job scheduling, workflow orchestration, alerting and notifications and so on.

It is hard to pick the right WLA solution because there are

  • 20+ solutions to compare
  • 10+ use cases where businesses can leverage these tools. Each use case may need to be investigated as they may have different criteria.
  • Migration-related issues to investigate. Most enterprises already have a WLA tool and would need to understand how to migrate their old configuration to a new tool.

This article evaluates the core capabilities and market presence of the top 8 WLA tools so buyers can identify the top tools in a data-driven manner and focus on their buying process.

Workload automation market leaders

VendorReviews
ActiveBatch4.6 based on 246 reviews
Redwood RunMyJobs4.7 based on 148 reviews
Stonebranch4.5 based on 85 reviews
Fortra’s JAMS4.6 based on 162 reviews
Tidal by Redwood4.7 based on 89 reviews
Fortra Automate Schedule 4.5 based on 149 reviews
Control-M4.4 based on 58 reviews
AutoSys4.4 based on 48 reviews

Buyers should consider market leaders while choosing a solution. The number of B2B reviews is correlated with market leadership. Out of the top 20 public B2B software companies by revenue, 8 (i.e., 40%) are among the top 20 companies regarding reviews on a review platform, TrustRadius.

In the workload automation space, the total number of B2B reviews and average scores of all vendors in G2 and Capterra 2 are provided in the above table.

We sorted companies first by sponsorship level, the vendors with links are sponsors, and then by their number of reviews.

Selecting a shortlist of top workload automation software

A capability-based review of all 20+ workload automation tools in the market will not be feasible. We used the 3-step screening procedure to prepare a preliminary vendor analysis shortlist: 

  1. The number of employees on LinkedIn: The number of employees is correlated with revenue, which is correlated with the overall success of firms. For long-term solutions, vendors with more workers can have greater resources and knowledge to support their products and services. We screened out vendors with less than 100 employees on LinkedIn.
  2. Financial health: Financial health and value can signify vendor success. Financially solid suppliers can invest in R&D, customer support, and other company resources to provide trustworthy, unique goods. We only selected vendors with at least 3 million dollars in funding or revenue.
  3. References from case studies: Finally, we examined case studies of how other companies used each vendor’s products and services to see the products’ real-world impact. We screened vendors without Fortune 500 references/case studies on their websites.

Workload Automation Feature Comparison

The data was gathered from the websites of the vendors. You can filter or sort Table 1 by low-code capability (i.e. Yes or NA) or other columns. 

ProductsLow-codeSupported coding languagesERP integrationsCloud applications&integrationsBig data integrations
ActiveBatchYesNA-Oracle Job Scheduler
-Microsoft Dynamics AX
-Crystel Reports -CyberArk Application Manager -Exchange Server -PowerShell -MS Azure -MS Sharepoint -MS Team Foundation Server
-SQL Server Scheduling -Hadoop -IBM Cognos BI -IBM DataStage -IBM PureData
Redwood RunMyJobsYes

-Python
-R
-And more than 25 coding languages
-Infor -SAP Business Warehouse -SAP Business Objects -SAP S4/HANA -Oracle E-Business Suite -Oracle JD Edwards -Oracle Enterprise One -Oracle Netsuite -Oracle Peoplesoft -Workday
-AWS Lambda -Amazon EC2 -Google Cloud -Kubernetes -MS Azure -VMware -Xen
-Apache Oozie -Cassandra -DistCP -Hadoop -IBM Cognos -Impala -Mesos -Redshift -Splunk -Snowflake
StonebranchYesPython-Peoplesoft
-SAP Business Objects
-SAP NetWeaver
-AWS EC2
-AWS Lambda
-Azure Blob
-Azure VM
-Apache Airflow
-Databricks
-Google BigQuery
-Hitachi Vantara
-Snowflake
Fortra's JAMSNANA
-Oracle EBS -SAP Enterprise Resource Planning -SAP Human Resources -SAP NetWeaver -SAP Supply Chain Management
-Amazon Lambda
-Amazon S3
-Azure Blob
-Azure Pipelines
-Hadoop
-IBM i (AS/400)
-Netezza
-SAS
-SCOM
-Snowflake
BMC Software Control-MYes-JSON
-Python
-SAP Business Warehouse -SAP ERP Central Component -SAP S/4 HANA -SAP Process Integration
-Apache Airflow
-Azure
-Google
-Databricks
-Snowflake
-Talend
-Kubernetes
-Alteryx Trifacta -AWS Glue DataBrew -Azure Data Factory -Hadoop -SQLServer -Redshift -Snowflake -PostgreSQL
Fortra Automate ScheduleYesNA
-Cron -IBM i agent -Oracle EBS -Robot Schedule -SAP NetWeaver -Windows Task Scheduler
-MS SQL Server
-PowerCenter


-Informatica
-Informatica Cloud
CA Technologies AutoSys by BroadcomYes-AutoSys Job Information Language-SAP Business Warehouse
-SAP Solution Manager
-Amazon RDS
-Azure
-Azure SQL Server
-Google Cloud
-Apache Oozie
-Hadoop
-Hadoop Distributed File System
-HIVE
-PIG
-SQOOP
Tidal by RedwoodYesNA
-Oracle ERP -Oracle E-Business -JD Edwards -Peoplesoft -SAP BW -SAP ERP -SAP S4/Hana
-AWS
-Azure
-Azure Blob
-S3
-Apache Airflow -Hadoop -Azure Data Factory -Google Big Query -IBM Cognos -Informatica -SAP BOBI

Table 1: Workload automation tools. The links in the table are provided for our sponsors.

Each platform has its strengths and weaknesses, so it’s important to evaluate them based on your enterprise’s needs. However, ActiveBatch and Redwood RunMyJobs list more ERP integrations and support more programming languages than other tools in the list. According to our research, WLA buyers should include ActiveBatch and Redwood RunMyJobs in their shortlist since they hold a strong market presence and offer the key features of a comprehensive WLA tool. 

Core workload automation capabilities are provided by all vendors

There are features provided by all tools in our shortlist, according to the vendor websites. We can refer to them as core workload automation features. These core capabilities can be listed as:

  • Multi-and hybrid cloud deployment environment support: According to the vendor websites, all six technologies support multi- and hybrid cloud deployments.
  • Core cloud platform integrations: All six technologies integrate with Amazon Web Services (AWS).
  • Core specializations in workload automation: All six technologies assist the following activities:
    • Cloud management
    • Data center management
    • Data management

Differentiating capabilities

Not all tools offer the following six capabilities, or they offer them differently. This could be because they do not provide these features or have chosen not to market this aspect of their offering. We can refer to these features as other capabilities of workload automation tools.

Table 1 above summarizes information about the other capabilities of WLA software. You can find the relevant information regarding these differentiating features:

  1. Low-code capability
  2. Supported coding languages
  3. ERP integrations
  4. Cloud platforms and applications integrations
  5. Big data integrations

6 Key features of workload automation tools explained

1. Deployment environment

Multi-cloud workload automation

The multi-cloud environment uses multiple public cloud services like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud. Multi-cloud workload automation tools can be used to solve multi-cloud challenges such as:

  • Compatibility: Different cloud providers can use different technologies, making application and service interoperability across cloud environments difficult.
  • Integration: Integration can be complex and time-consuming if cloud providers use different APIs and integration methods. Multi-cloud WLA tools can automate workflows between AWS, Azure, Google Cloud, IBM cloud, and enterprise resource planning systems (ERP) such as SAP ERP.
  • Management: Multi-cloud management can demand resource coordination across many cloud providers. This can take time and require specific expertise and tools.

Hybrid cloud workload automation

In hybrid cloud services, companies use private cloud and/or on-premise data centers in addition to one or more public cloud environments. Therefore hybrid clouds can sometimes include multi-cloud environments as well.

Similar multi-cloud challenges, companies can face compatibility, integration, and management problems across:

  • Public cloud
  • Private cloud 
  • On-premises data center

For example, Bayer in Italia used a workload automation tool to integrate operations between Microsoft SQL and Oracle database platforms into its data centers.3

A hybrid cloud user can use multiple public clouds next to its private cloud and data centers. For example, Redwood RunMyJobs is specialized in integrating public cloud services. It is a tool for multi-cloud environments. It can provide extensive integration between SaaS applications, including tools for public cloud environments, which makes it a good tool for multi-cloud environments. But it also offers services integrating private and public clouds, making it a hybrid cloud tool.

This illustrates the difference between hybrid and multi-cloud. In the hybrid cloud,  there are traditional on-premises data centers next to the cloud. In multi-cloud applications connect various cloud services operating independently.

Figure 2. Hybrid cloud vs. Multi-cloud operations.4

2. Low-code capability

Low-code WLA tools allow citizen developers to automate operations. These tools usually feature a graphical user interface or pre-made elements for automating processes and creating rules. 

Benefits of Low/no-code WLA include: 

  • Improved accessibility: Low-code features can let non-programmers use WLA tools. By 2024, approximately 65% of application development will be low-code. 
  • Greater speed: Low-code features enable faster automation processes, rule creation, and deployment. Low-code solutions save development time by 90%.
  • Reduced risk: Low-code capabilities can help reduce the risk of errors and bugs in automation workflows and rules because users do not need to write custom code.

3. Supported coding languages

For WLA tools, supporting several code languages is important because it means:

  • Improved flexibility: Multiple coding languages allow workload automation tools to automate more operations and processes. This is especially valuable for firms that utilize numerous programming languages or need to automate operations and processes using multiple languages.
  • Enhanced interoperability: Workload automation tools that support several coding languages can aid system and application integration and interoperability. This can help firms automate data transmission between systems and apps.
  • Greater scalability: Workload automation tools that support several coding languages allow users to scale automation as workloads increase. This is especially valuable for firms with complicated automation needs or many tasks and processes.
  • Improved efficiency: A workload automation tool that supports different coding languages lets users choose the optimal language for the task, making automation more efficient.

4. ERP Integrations

Integration of a workload automation tool with an ERP system can be crucial for obtaining the following benefits:

  • Improved efficiency: Workload automation software can help boost ERP system efficiency by automating resource management and coordinating duties. 
  • Enhanced visibility: Workload automation software coupled with ERP systems can provide real-time visibility into tasks and processes, helping detect bottlenecks and inefficiencies.
  • Greater flexibility: ERP modules can be automated with an integrated workload automation tool. This lets companies modify and optimize system usage.

ERP integrations can be categorized as follows:

5. Cloud platform applications and integrations

WLA tools can integrate different cloud environments and applications. Some WLA solutions can automate cloud chores on AWS and Microsoft Azure. Others can also link Azure Blob to Kubernetes. In cloud environments, WLA software can automate:

  • Virtual machines 
  • Storage
  • Networking resource provisioning, configuration, and scaling
  • Cloud management: Workload automation software can automate tasks and processes related to cloud resource management and deployment, such as:
    • Provisioning and configuring cloud resources 
    • Deploying and managing cloud-based applications 
    • Monitoring cloud-based workloads

6. Big data integrations

Workload automation-big data integration is important for the following reasons:

  • Data integration: Workload automation tools can automate tasks and processes associated with data integration from various sources, such as:
    • Structured and unstructured data. ~90% of an organization’s data is unstructured, necessitating various applications to turn them into organized formats.
The figure illustrates that data preparation takes ~22% and data cleansing ~16% of data analysts' time.

Figure 3. Data analysts spent ~38% of their time preparing and cleaning data.5

  • Data transfer: Workload automation platforms can automate tasks and processes associated with data movement, such as:
    • Data transfer between various systems and applications
    • Load balancing of data streams. Load balancing is the process of distributing incoming network traffic across multiple backend servers. It is also referred to as a server farm or pool.
  • Data governance: Workload automation software can automate data governance tasks and processes such as:
    • Enforcing data quality standards 
    • Tracking data lineage
    • Managing data security and compliance

Similar Tools

It is also important to note that workload automation tools are often used interchangeably with enterprise scheduling tools. Enterprise scheduling tools focus on task and job scheduling within specific environments, workload automation tools offer broader capabilities for automating complex workflows and orchestrating tasks across multiple systems, while job scheduling tools specialize in managing recurring or batch jobs efficiently. However, it’s worth noting that there can be an overlap in functionality between these tools, and the terminology may vary depending on the context and specific software solutions.

Explore vendor lists for:

If you already have some workload automation tools in your mind or if you want to see the alternatives, check out:

Transparency statement

AIMultiple serves numerous technology vendors, including Redwood which provides Active Batch, RunMyJobs, and Tidal.

Disclaimers

  • The prices of the WLA tools are not listed in the table because vendors give their customers customized quotes based on usage. 
  • Because all workload automation software provides job scheduling capabilities, job scheduling is not considered as a difference in the table.
  • All workload automation tools provide managed file transfer. Thus, it is not considered in the table.
  • We may have missed some workload automation tools that satisfied the screening criteria. In that case, please leave a comment, and we’ll consider adding them.

If you have any additional queries regarding WLA tools and best practices, do not hesitate to get in touch with us at:

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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Drafted by
Altay Ataman
Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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