Cloudera Distribution for Hadoop and IBM Netezza Performance Server are robust data solutions competing in the realm of big data analytics and warehousing. Users generally favor Cloudera for its rich feature set, particularly in security and data management, while Netezza is preferred for its high performance and simplicity, especially in environments requiring speed and efficiency.
Features: Cloudera shines with enterprise security, rapid data processing, and a user-friendly Cloudera Manager for administration. It offers flexible tools like Impala and Sentry. Netezza impresses with an MPP architecture, ease of use with low maintenance needs, high availability, and fast query execution.
Room for Improvement: Cloudera faces challenges with scalability, configuration, and pricing. Its deployment complexity and stability issues, particularly with Apache Kudu, need addressing. Netezza requires better concurrency support, enhanced cloud functionalities, and improved scalability and user interface.
Ease of Deployment and Customer Service: Cloudera offers on-premises and hybrid cloud deployment flexibility, while Netezza provides a straightforward appliance-based approach. Netezza is praised for excellent customer service and efficient support. Cloudera's support receives mixed reviews, with some highlighting responsiveness and others noting inconsistencies.
Pricing and ROI: Cloudera's pricing is perceived as high, with escalating costs impacting small businesses. Despite this, a significant ROI is observed. Netezza, though also expensive upfront, offers value with high performance and low maintenance, making it cost-effective for large-volume data operations.
The technical support is quite good and better than IBM.
Technical support is very costly for me, accounting for twenty-five to thirty percent of the product cost.
It is provided as a pre-configured box, and scaling is not an option.
We faced challenges but overcame those challenges successfully.
Integrating with Active Directory, managing security, and configuration are the main concerns.
The cloud version is only available in AWS, and in the Middle East, it is not well-developed in the Azure environment.
It can be deployed on-premises, unlike competitors' cloud-only solutions.
This is the only solution that is possible to install on-premise.
It operates as a high-speed data warehouse, which is essential for handling big data.
| Product | Market Share (%) |
|---|---|
| Cloudera Distribution for Hadoop | 15.1% |
| IBM Netezza Performance Server | 5.0% |
| Other | 79.9% |
| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 9 |
| Large Enterprise | 31 |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 5 |
| Large Enterprise | 33 |
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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