AuraQuantic and Apache Airflow operate in different domains, with AuraQuantic focusing on low-code automation and Apache Airflow on workflow orchestration. AuraQuantic seems to have an advantage in broader automation capabilities and ease of use, while Apache Airflow excels in precision and complex data pipeline management.
Features: AuraQuantic offers a comprehensive suite for business process automation, integration capabilities with IoT devices, and a user-friendly interface for non-technical users. Its low-code approach allows rapid application development and digitalization of business processes. Apache Airflow provides extensive workflow scheduling, rich integration support for various data sources, and advanced DAG-based visualizations for managing complex data pipelines.
Room for Improvement:AuraQuantic could enhance technical flexibility to cater to more complex customization needs, improve scalability for very large enterprises, and expand its community support for better collaborative development. Apache Airflow could simplify its deployment challenges to reduce the technical expertise required, improve its user interface for non-technical stakeholders, and offer more built-in connectors for diverse data services to enhance its plug-and-play functionality.
Ease of Deployment and Customer Service: AuraQuantic provides a straightforward cloud-based deployment with seamless customer service, making it accessible to non-technical users. Apache Airflow requires a more involved technical setup and infrastructure, which can be challenging without expert knowledge, but offers strong community support to resolve deployment issues.
Pricing and ROI: AuraQuantic's pricing is competitive, with a quick ROI due to its ease of use and rapid deployment. Apache Airflow, being open-source, presents a cost advantage in licensing fees but may incur higher setup costs due to the need for skilled personnel, potentially impacting its ROI over time.
Forums and community resources like Stack Overflow are helpful.
There is enough documentation available, and the community support is good.
The solution is very scalable.
Apache Airflow scales well, especially when deployed in Kubernetes environments.
I would rate its stability at nine out of ten.
Apache Airflow is stable and I have not experienced significant issues.
I would rate the stability of the solution as ten out of ten.
It is not suitable for real-time ETL tasks.
There is no dashboard for us to check all the Directed Acyclic Graphs (DAGs); a dashboard would help us analyze the work better.
If we desire to add custom messengers or a rest API, those options are unavailable.
It is a sub-feature and not an individual purchase.
I prefer using the open-source version rather than the enterprise version, which helps manage costs.
Apache Airflow is a community-based platform and is not a licensed product.
Reliability is good, and when integrated with Kubernetes, it performs better compared to on-premises environments.
Apache Airflow is an open-source platform that allows easy integration with AWS, Azure, and Google Cloud Platform.
We can create notifications for successful or failed tasks, providing a practical way to monitor our workflows.
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.”
AuraQuantic is a digital platform designed for business users to easily and rapidly build unlimited processes and applications to automate end-to-end operations, reducing costs and optimizing productivity.
AuraQuantic is a no-code platform for building the enterprise solutions that drive Digital Transformation.
Delight users with attractive interfaces across multiple devices and deliver the best user experience. Respond immediately to their ever-changing needs with the agility provided by the platform and its no-code changes on the fly.
This is the most powerful part of any application. This is why AuraQuantic offers a long list of built-in, no-code functionalities.
To manage application and process data models, AuraQuantic provides a visual data model designer and supports importing data schemas.
Access rights management (to apps and app development), Application metadata collection, Application performance monitoring, Application works dashboard, Custom ‘guardrails’ for practitioners/developers, Role-based access control to data and services for app dev, Multiple practitioners/developers for a single app and across the platform.
Digital Decisioning features aim to inform and automate operational decisions. These decisions continue to increase in amount and complexity due to growing customer demands. Business decision automation is a must to keep up with ever-changing customer needs.
Thanks to business activity data collection, using custom applications built with AuraQuantic, the organization is empowered to carry out accurate analysis and act smart by leveraging business insights.
API REST, API SOAP, API DLL
Exposing APIs (process/application logic and decision systems)
Connector builder
REST and SOAP web services connector
External database connectors (Adapters Servers, scripts and stored procedures execution)
.Net Assembly connector Connectors with Artificial Intelligence services (AI)
Robotic Process Automation (RPA) service connectors
More built-in connectors (50+)
Microsoft Office 365, Google Suite, SAP…
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