Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
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.
Technical support is very costly for me, accounting for twenty-five to thirty percent of the product cost.
Azure Data Factory is highly scalable.
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.
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.
When using Git services, there are challenges with linked services and triggers getting overridden when moving between different environments (Dev, UAT, Prod).
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.
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.
It operates as a high-speed data warehouse, which is essential for handling big data.
Company Size | Count |
---|---|
Small Business | 31 |
Midsize Enterprise | 19 |
Large Enterprise | 55 |
Company Size | Count |
---|---|
Small Business | 9 |
Midsize Enterprise | 5 |
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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