Apache Airflow vs WorkflowGen comparison

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Apache Logo
13,927 views|10,035 comparisons
96% willing to recommend
WorkflowGen Logo
158 views|127 comparisons
100% willing to recommend
Comparison Buyer's Guide
Executive Summary

We performed a comparison between Apache Airflow and WorkflowGen based on real PeerSpot user reviews.

Find out in this report how the two Business Process Management (BPM) solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
To learn more, read our detailed Apache Airflow vs. WorkflowGen Report (Updated: April 2024).
768,415 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"Apache Airflow is easy to use and can monitor task execution easily. For instance, when performing setup tasks, you can conveniently view the logs without delving into the job details.""Development on Apache Airflow is really fast, and it's easy to use with the newer updates. Everything is in Python, so it's not hard to understand. They also have a graphical view, so if you are not a programmer and you are just an administrator, you can easily track everything and see if everything is working or not.""We have been quite satisfied with the stability of the solution.""Since the solution is programmatic, it allows users to define pipelines in code rather than drag and drop.""This is a simple tool to automate using Python.""Every feature in Apache Airflow is valuable. The number of operators and features I've used are mainly related to connectivity services and integrated services because I primarily work with GCP.""The most valuable feature of Apache Airflow is creating and scheduling jobs. Additionally, the reattempt at failed jobs is useful.""The product is stable."

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"We use it a lot for creating workflows to transfer materials between plants, which is a signature part of what we do."

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Cons
"The documentation must be improved.""UI can be improved with additional user-friendly features for non-programmers and for fewer coding practitioner requirements.""The scalability of the solution itself is not as we expected. Being on the cloud, it should be easy to scale, however, it's not.""The solution could be improved by simplifying the integration process.""The platform's stability needs improvement, particularly regarding occasional interruptions due to networking issues.""It would be beneficial to improve the pricing structure.""The automation capabilities could be improved; a visual workflow designer and a graphical tool to reduce coding would be very helpful. But for now, it's sufficient for our simple workflows.""One specific feature that is missing from Airflow is that the steps of your workflow are not pipelined, meaning the stageless steps of any workflow. Not every workflow can be implemented within Airflow."

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"This solution needs to be more customizable."

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Pricing and Cost Advice
  • "Apache Airflow is a free solution that can be downloaded and ready for use at any moment."
  • "The pricing for the product is reasonable."
  • "Although Airflow is open source software, there's also commercial support for it by Astronomer. We personally don't use the commercial support, but it's always an option if you don't mind the extra cost."
  • "We are using the open-source version of Apache Airflow."
  • "We use a community edition of Apache Airflow. It is open source and free."
  • "Apache Airflow is open-source and free of charge."
  • "It's open-source."
  • "The solution is open source so is free."
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    8.0
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    Also Known As
    Airflow
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    Overview

    Apache Airflow is an open-source workflow management system (WMS) that is primarily used to programmatically author, orchestrate, schedule, and monitor data pipelines as well as workflows. The solution makes it possible for you to manage your data pipelines by authoring workflows as directed acyclic graphs (DAGs) of tasks. By using Apache Airflow, you can orchestrate data pipelines over object stores and data warehouses, run workflows that are not data-related, and can also create and manage scripted data pipelines as code (Python). 

    Apache Airflow Features

    Apache Airflow has many valuable key features. Some of the most useful ones include:

    • Smart sensor: In Apache Airflow, tasks are executed sequentially. The smart sensors are executed in bundles, and therefore consume fewer resources.
    • Dockerfile: By using Apache Airflow’s dockerfile feature, you can run your business’s Airflow code without having to document and automate the process of running Airflow on a server. 
    • Scalability: Because Apache Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers, you can easily scale it. 
    • Plug-and-play operators: With Apache Airflow, you can choose from several plug-and-play operators that are ready to execute your tasks on many third-party services.

    Apache Airflow Benefits

    There are many benefits to implementing Apache Airflow. Some of the biggest advantages the solution offers include:

    • User friendly: Using Apache Airflow requires minimal python knowledge to get started.
    • Intuitive user interface: The Apache Airflow user interface enables you to visualize pipelines running in production, monitor progress, and also troubleshoot issues when needed.
    • Easy integration: Apache Airflow can easily be integrated with cloud platforms (Google, AWS, Azure, etc).
    • Visual DAGs: Apache Airflow’s visual DAGs provide data lineage, which facilitates debugging of data flows and also aids in auditing and data governance. 
    • Flexibility: Apache Airflow provides you with several ways to make DAG objects more flexible. At runtime, a context variable is passed to each workflow execution, which is quickly incorporated into an SQL statement that includes the run ID, execution date, and last and next run times.
    • Multiple deployment options: With Apache Airflow, you have several options for deployment, including self-service, open source, or a managed service.
    • Several data source connections: Apache Airflow can connect to a variety of data sources, including APIs, databases, data warehouses, and more.  

    Reviews from Real Users

    Below are some reviews and helpful feedback written by PeerSpot users currently using the Apache Airflow solution.

    A Senior Solutions Architect/Software Architect says, “The product integrates well with other pipelines and solutions. The ease of building different processes is very valuable to us. The difference between Kafka and Airflow, is that it's better for dealing with the specific flows that we want to do some transformation. It's very easy to create flows.”

    An Assistant Manager at a comms service provider mentions, “The best part of Airflow is its direct support for Python, especially because Python is so important for data science, engineering, and design. This makes the programmatic aspect of our work easy for us, and it means we can automate a lot.”

    A Senior Software Engineer at a pharma/biotech company comments that he likes Apache Airflow because it is “Feature rich, open-source, and good for building data pipelines.”

    Immediately accelerate business process adaptability with fluid workflow automation. Use the WorkflowGen .NET workflow software's low code environment to maximize the efficiency of process designers and developers.

    Automate any type of human and system-based enterprise process within a battle-tested infrastructure.

    Customize and integrate your workflow apps to meet your requirements in a highly configurable environment.

    Engage process participants with a full-featured workflow portal, native mobile apps, and email approvals, or through seamless integration with your own web apps.

    Leverage a solution used by Fortune 500 companies for worldwide business-critical applications.

    Sample Customers
    Agari, WePay, Astronomer
    Comcast, Deloitte, Mitsui & Co Ltd, Sanofi Pasteur, Textron, XL Group. WorkflowGen accelerates business process adaptability in 70 countries for 500+ organizations and 1,000,000 users.
    Top Industries
    REVIEWERS
    Comms Service Provider21%
    Financial Services Firm21%
    Media Company16%
    Pharma/Biotech Company5%
    VISITORS READING REVIEWS
    Financial Services Firm22%
    Computer Software Company14%
    Manufacturing Company7%
    Retailer5%
    No Data Available
    Company Size
    REVIEWERS
    Small Business29%
    Midsize Enterprise6%
    Large Enterprise65%
    VISITORS READING REVIEWS
    Small Business16%
    Midsize Enterprise12%
    Large Enterprise73%
    No Data Available
    Buyer's Guide
    Apache Airflow vs. WorkflowGen
    April 2024
    Find out what your peers are saying about Apache Airflow vs. WorkflowGen and other solutions. Updated: April 2024.
    768,415 professionals have used our research since 2012.

    Apache Airflow is ranked 2nd in Business Process Management (BPM) with 31 reviews while WorkflowGen is ranked 53rd in Business Process Management (BPM). Apache Airflow is rated 8.0, while WorkflowGen is rated 7.6. The top reviewer of Apache Airflow writes "Enable seamless integration with various connectivity and integrated services, including BigQuery and Python operators ". On the other hand, the top reviewer of WorkflowGen writes "Good for automatically triggering workflows, but needs to be more customizable". Apache Airflow is most compared with Camunda, Informatica Cloud API and App Integration, IBM BPM, IBM Business Automation Workflow and AWS Step Functions, whereas WorkflowGen is most compared with . See our Apache Airflow vs. WorkflowGen report.

    See our list of best Business Process Management (BPM) vendors.

    We monitor all Business Process Management (BPM) reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.