OpenText ProVision and Apache Airflow are competing in business process management and workflow orchestration. Apache Airflow holds the upper hand due to its strong scalability and extensibility in data engineering tasks.
Features: OpenText ProVision provides comprehensive enterprise modeling, intuitive solutions for business architecture, and structured visualization tools. Apache Airflow offers ease of integration with data sources, efficient scheduling, and a flexible orchestration environment supporting complex workflows.
Ease of Deployment and Customer Service: OpenText ProVision ensures a straightforward deployment experience with enterprise-level support resources. Apache Airflow requires more technical expertise for deployment but benefits from a highly active community for troubleshooting and feature development. OpenText ProVision focuses on comprehensive customer support, while Apache Airflow promotes collaborative community problem-solving.
Pricing and ROI: OpenText ProVision involves higher setup costs, reflecting its enterprise focus, but offers substantial ROI through improved process efficiency. Apache Airflow's open-source nature results in economical setup costs, and although it demands significant time and customization, it leads to favorable ROI by efficiently handling large-scale data workflows.
| Product | Market Share (%) |
|---|---|
| Apache Airflow | 5.5% |
| OpenText ProVision | 0.4% |
| Other | 94.1% |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 3 |
| Large Enterprise | 24 |
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.”
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.
