Microsoft Parallel Data Warehouse and IBM Netezza Performance Server are key rivals in the data warehousing sector. IBM Netezza seems to have an edge due to its ease of use and quick deployment, appealing to clients handling large volumes efficiently.
Features: Microsoft Parallel Data Warehouse offers seamless Azure integration, extensive Microsoft ecosystem compatibility, and strong data handling capabilities ideal for large projects. Its integration with SSIS and Power BI enhances its utility for comprehensive data solutions. IBM Netezza Performance Server features high-speed parallel processing, efficient management of large data sets without the need for complex configurations, and reduced administrative needs due to its appliance format simplifying deployments.
Room for Improvement: Microsoft users indicate a need for better cross-platform compatibility, hardware utilization enhancements, and cost reductions. Concerns about scalability and real-time updates persist. IBM Netezza requires better scalability, improved concurrent query handling, and enhanced integration with new technologies, alongside addressing infrastructure rigidity and support costs.
Ease of Deployment and Customer Service: Microsoft Parallel Data Warehouse offers multiple deployment options, including cloud and hybrid environments, with Azure-related expertise needing improvement. IBM Netezza offers straightforward setup and simplicity, largely dependent on IBM's expertise due to its proprietary system components.
Pricing and ROI: Microsoft Parallel Data Warehouse presents competitive pricing for large enterprises but is considered expensive by smaller firms. It promises a strong ROI through efficient data management. IBM Netezza justifies its higher cost by offering significant simplicity and performance benefits, with expensive support costs offset by long-term, high-performance returns.
Technical support is very costly for me, accounting for twenty-five to thirty percent of the product cost.
They are responsive and get back to us.
I would rate my experience with technical support around six on a scale of 1 to 10 because I have not had a particular experience with technical support.
It is provided as a pre-configured box, and scaling is not an option.
We go from a couple of users to tons of users all the time, and it scales and handles things really well.
I give the scalability an eight out of ten, indicating it scales well for our needs.
As a consultant, we hire additional programmers when we need to scale up certain major projects.
Microsoft Parallel Data Warehouse is stable for us because it is built on SQL Server.
The cloud version is only available in AWS, and in the Middle East, it is not well-developed in the Azure environment.
Addressing the cost would be the number one area for improvement.
It would be better to release patches less frequently, maybe once a month or once every two months.
When there are many users or many expensive queries, it can be very slow.
Microsoft Parallel Data Warehouse is very expensive.
It operates as a high-speed data warehouse, which is essential for handling big data.
The columnstore index enhances data query performance by using less space and achieving faster performance than general indexing.
There's a feature that allows users to set alerts on triggers within reports, enabling timely actions on pending applications and effectively reducing waiting time.
Its scalability is impressive as it scales up and down really well.
| Product | Mindshare (%) |
|---|---|
| Microsoft Parallel Data Warehouse | 2.4% |
| IBM Netezza Performance Server | 4.4% |
| Other | 93.2% |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 5 |
| Large Enterprise | 33 |
| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 6 |
| Large Enterprise | 22 |
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.
The traditional structured relational data warehouse was never designed to handle the volume of exponential data growth, the variety of semi-structured and unstructured data types, or the velocity of real time data processing. Microsoft's SQL Server data warehouse solution integrates your traditional data warehouse with non-relational data and it can handle data of all sizes and types, with real-time performance.
We monitor all Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
