TIBCO BusinessWorks and Azure Data Factory compete in the integration tools category. Azure Data Factory seems to have the upper hand due to its cost-effective cloud-native operations and ease of use.
Features: TIBCO BusinessWorks is renowned for its stability, transformation capabilities, and extensive adapter support, making it robust for integration tasks. It features a low-code platform and debugging console for simplified development. Azure Data Factory stands out for its ease of use in cloud-based ETL processes with a visual drag-and-drop interface, comprehensive integration within the Azure ecosystem, and built-in connectors for broad connectivity.
Room for Improvement: TIBCO BusinessWorks should enhance its cloud capabilities, simplify pricing models, and improve user-friendliness and integration support. Azure Data Factory could benefit from simplifying its interface, expanding connector support, and enhancing real-time data processing. Addressing pricing complexity and improving transformation capabilities would also be beneficial.
Ease of Deployment and Customer Service: TIBCO BusinessWorks typically requires more extensive setup due to its on-premises or hybrid configurations compared to Azure Data Factory's cloud-based, easily scalable nature. TIBCO's customer service is mixed with noted delays, whereas Azure Data Factory benefits from the efficient support standard in cloud solutions.
Pricing and ROI: TIBCO BusinessWorks is considered expensive with high licensing and deployment costs, ideal for larger enterprises. Its ROI is driven by reliability and integration features. Azure Data Factory employs a pay-as-you-go pricing model, making costs fluctuate based on usage but generally offering competitive, transparent pricing that scales with demand, providing more cost control flexibility.
Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
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.
Customer service is very helpful.
Azure Data Factory is highly scalable.
It is not like AWS where I can add memory or more servers.
The solution has a high level of stability, roughly a nine out of ten.
It is stable, however, every now and then, it just ends.
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.
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 learning curve takes time compared to webMethods.
They should ensure that what was working in the previous version must also work in the new version of BW six.
The pricing is cost-effective.
It is considered cost-effective.
Pricing is for an enterprise application, so the company pays for it with a company license.
It connects to different sources out-of-the-box, making integration much easier.
The platform excels in handling major datasets, particularly when working with Power BI for reporting purposes.
The interface of Azure Data Factory is very usable with a more interactive visual experience, making it easier for people who are not as experienced in coding to work with.
When I have an architecture designed to plug in the service itself with BW, it makes things much easier.
It's a great software application for the middleware use cases to connect the front channels to the back ends in a secure and safer way.
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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