Apache Airflow and Studio Creatio are tools focused on automation, with Airflow being more suited for data workflows requiring scripting abilities, while Studio Creatio offers a low-code environment for business process automation. Airflow holds an advantage in scenarios requiring detailed data pipeline control, whereas Creatio is preferred for straightforward business management.
Features: Apache Airflow offers Python-based configuration, extensive flexibility, and DAGs for visual workflow management. It integrates efficiently with other solutions, benefiting from open-source community support. Studio Creatio provides an easy-to-use low-code platform ideal for business process automation and customer relationship management.
Room for Improvement: Apache Airflow faces criticism for its limited cyclical workflow support and visualization tools, with suggestions for better versioning and real-time job features. Studio Creatio could benefit from enhanced UI customization, more diverse technology integration, and improved multilingual support.
Ease of Deployment and Customer Service: Apache Airflow can be deployed locally or in the cloud and enjoys substantial community support despite lacking formal paid support. Studio Creatio offers on-premises and hybrid cloud deployments, although customer service experiences are mixed and could improve.
Pricing and ROI: Apache Airflow is an open-source, cost-effective option for data orchestration, offering high ROI through its flexibility and applicability. Studio Creatio requires licensing, yet it is competitively priced among low-code solutions and is a reasonable investment for business automation.
Forums and community resources like Stack Overflow are helpful.
There is enough documentation available, and the community support is good.
The customer support is quite helpful and the turnaround time is within 24 hours to 48 hours based on the priority of the request.
Apache Airflow scales well, especially when deployed in Kubernetes environments.
The solution is very scalable.
Apache Airflow is stable and I have not experienced significant issues.
I would rate the stability of the solution as ten out of ten.
I would rate its stability at nine out of ten.
It is quite stable, clean, and a steady platform.
It is not suitable for real-time ETL tasks.
The start date in Apache Airflow is also confusing because it is not straightforward. If you want it to start today, you should give tomorrow's date.
There is no dashboard for us to check all the Directed Acyclic Graphs (DAGs); a dashboard would help us analyze the work better.
It is a workflow automation process and enterprise-grade application where an understanding of the platform is essential to use Studio Creatio.
I prefer using the open-source version rather than the enterprise version, which helps manage costs.
It is a sub-feature and not an individual purchase.
Apache Airflow is a community-based platform and is not a licensed product.
Apache Airflow is an open-source platform that allows easy integration with AWS, Azure, and Google Cloud Platform.
Reliability is good, and when integrated with Kubernetes, it performs better compared to on-premises environments.
We can create notifications for successful or failed tasks, providing a practical way to monitor our workflows.
It supports all the horizontal and vertical scaling needs, with the ability to support from a minimum of 10 users to thousands of users without any lag in response.
| Product | Market Share (%) |
|---|---|
| Apache Airflow | 3.5% |
| Studio Creatio | 1.0% |
| Other | 95.5% |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 3 |
| Large Enterprise | 24 |
| Company Size | Count |
|---|---|
| Small Business | 11 |
| Midsize Enterprise | 2 |
| Large Enterprise | 1 |
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:
Apache Airflow Benefits
There are many benefits to implementing Apache Airflow. Some of the biggest advantages the solution offers include:
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.”
Studio Creatio is a no-code agentic platform to build applications and AI agents with natural language and visual designers.
Studio Creatio, Enterprise Edition is the unique synergy of business processes management and case management technologies that provide organizations with powerful tools to easily manage and optimize business processes.
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.
