Azure Data Factory and Alteryx Designer compete in the data integration and transformation space. Azure Data Factory appears to have the upper hand due to its extensive integration capabilities and scaling options.
Features: Azure Data Factory offers data flow orchestration, integration with GitHub, and support for SAP services. It also features over 100 built-in connectors and strong security integration with the Azure ecosystem. Alteryx Designer is recognized for its ease of use, drag-and-drop functionality, and adaptability in creating workflows. It offers real-time data analysis capabilities and seamlessly integrates with various data sources.
Room for Improvement: Azure Data Factory needs improved integration with Azure Machine Learning and more third-party connectors. Users suggest enhancements in performance, documentation, and simplifying the pricing model. Alteryx Designer could improve its web governance, offer simpler reporting tools, and provide a more competitive pricing structure. The tool's high cost and license scalability remain key drawbacks.
Ease of Deployment and Customer Service: Azure Data Factory is deployed across public and private clouds, requiring Azure expertise and improved documentation. Alteryx Designer is mainly implemented on-premises, resulting in a more static deployment strategy. Both tools receive mixed reviews on customer service, with Azure Data Factory benefiting from community support, while Alteryx Designer struggles with response times and documentation quality.
Pricing and ROI: Azure Data Factory uses a pay-as-you-go model, which can be cost-effective for various workloads despite its complex pricing. Users report significant ROI via reduced data integration costs. Alteryx Designer is considered expensive, particularly as usage increases, hindering ROI for smaller clients, although it offers automation and analytics benefits.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
There are areas where they need to improve response time and overall competence.
The technical support is responsive and helpful
The technical support from Microsoft is rated an eight out of ten.
The technical support for Azure Data Factory is generally acceptable.
Azure Data Factory is highly scalable.
The solution has a high level of stability, roughly a nine out of ten.
There is a problem with the integration with third-party solutions, particularly with SAP.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
The inability to connect local VMs and local servers into the data flow is a limitation that prevents giving Azure Data Factory a perfect score.
It's cheaper than Palantir, but even Alteryx is too much for small clients.
The pricing is cost-effective.
It is considered cost-effective.
The main valuable aspect is the simplicity of use across all features.
The orchestration features in Azure Data Factory are definitely useful, as it is not only for Azure Data Factory; we can also include DataBricks and other services for integrating the data solution, making it a very beneficial feature.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
It connects to different sources out-of-the-box, making integration much easier.
| Product | Market Share (%) |
|---|---|
| Azure Data Factory | 3.0% |
| Alteryx Designer | 1.5% |
| Other | 95.5% |
| Company Size | Count |
|---|---|
| Small Business | 12 |
| Midsize Enterprise | 3 |
| Large Enterprise | 17 |
| Company Size | Count |
|---|---|
| Small Business | 31 |
| Midsize Enterprise | 19 |
| Large Enterprise | 57 |
Azure Data Factory efficiently manages and integrates data from various sources, enabling seamless movement and transformation across platforms. Its valuable features include seamless integration with Azure services, handling large data volumes, flexible transformation, user-friendly interface, extensive connectors, and scalability. Users have experienced improved team performance, workflow simplification, enhanced collaboration, streamlined processes, and boosted productivity.
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