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Our stakeholders and clients have expressed satisfaction with Azure Data Factory's efficiency and cost-effectiveness.
On a scale of one to ten, I would rate the technical support as nine.
The technical support from Microsoft is rated an eight out of ten.
The technical support is responsive and helpful
Technical support is very costly for me, accounting for twenty-five to thirty percent of the product cost.
Azure Data Factory is highly scalable.
I did not experience scalability issues.
It is provided as a pre-configured box, and scaling is not an option.
The solution has a high level of stability, roughly a nine out of ten.
I have been using Azure Data Factory for a very long time, and I did not find too many issues.
The ability to handle the largest volumes of data is another concern; if I have to manage more than one terabyte of data every day, I am not comfortable dealing with Azure Data Factory and had to switch to Oracle Data Integrators (ODI) because it lacks performance features.
Incorporating more dedicated API sources to specific services like HubSpot CRM or Salesforce would be beneficial.
Sometimes, the compute fails to process data if there is a heavy load suddenly, and it doesn't scale up automatically.
The cloud version is only available in AWS, and in the Middle East, it is not well-developed in the Azure environment.
The pricing is cost-effective.
It is considered cost-effective.
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.
Regarding the integration feature in Azure Data Factory, the integration part is excellent; we have major source connectors, so we can integrate the data from different data sources and also perform basic transformation while transforming, which is a great feature in Azure Data Factory.
It operates as a high-speed data warehouse, which is essential for handling big data.


| Company Size | Count |
|---|---|
| Small Business | 31 |
| Midsize Enterprise | 21 |
| Large Enterprise | 63 |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 6 |
| Large Enterprise | 33 |
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.
IBM Netezza Performance Server offers high performance, scalability, and minimal maintenance. It seamlessly integrates SQL for efficient data processing, making it ideal for enterprise data warehousing needs.
IBM Netezza Performance Server is known for its outstanding data processing capabilities. Its integration of FPGA technology, compression techniques, and partitioning optimizes query execution and scalability. Users appreciate its appliance-like architecture for straightforward deployment, distributed querying, and high availability, significantly boosting operations and analytics capabilities. However, there are areas for improvement, particularly in handling high concurrency, real-time integration, and specific big data functionalities. Enhancements in database management tools, XML integration, and cloud options are commonly desired, along with better marketing and community engagement.
What are the key features of IBM Netezza Performance Server?Industries rely on IBM Netezza Performance Server for robust data warehousing solutions, particularly in sectors requiring intensive data analysis such as finance, retail, and telecommunications. Organizations use it to power business intelligence tools like Business Objects and MicroStrategy for customer analytics, establishing data marts and staging tables to efficiently manage and update enterprise data. With the capacity to handle large volumes of compressed and uncompressed data, it finds numerous applications in on-premises setups, powering data mining and reporting with high reliability and efficiency.
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