HPE Data Fabric and Cloudera Data Platform are both heavyweights in the big data management arena. HPE Data Fabric holds a slight advantage in ease of use with its bundled ecosystem, while Cloudera excels in integration and flexibility for complex workloads.
Features: HPE Data Fabric offers a robust file system with NFS functionalities and the ability to support a global namespace through MapR-FS. It also includes MapR-DB for fast data updates. Cloudera Data Platform, on the other hand, integrates seamlessly with Ranger for security and NiFi for streaming services. It provides decoupled storage and compute, enabling innovative flexibility and making it well-suited for analytics and machine learning workloads.
Room for Improvement: HPE Data Fabric could enhance integration with third-party tools and improve cloud adaptability. Challenges include the complex manual deployment processes and lack of full Kerberos support. Cloudera Data Platform can better support AI workloads and streamline its complex tool integration. Faster support for the latest Apache releases and innovations in cloud management would significantly improve Cloudera's offerings.
Ease of Deployment and Customer Service: HPE Data Fabric is typically used on-premises, complicating cloud integration. Customer service has seen mixed reviews, particularly after its acquisition. Cloudera Data Platform supports hybrid cloud environments, adding deployment flexibility, but faces criticism for slow customer support response times. HPE has worked on improving post-acquisition support, whereas Cloudera's service integration complexity can affect deployment ease.
Pricing and ROI: HPE Data Fabric offers pricing flexibility, particularly for existing customers, but costs can rise for features like MapR-DB. Users find value in the usage-based models but struggle to quantify ROI without full implementation. Cloudera Data Platform's pricing structure is complex yet often less expensive than traditional systems like Oracle. The potential for ROI exists by leveraging Cloudera’s full feature set, although early quantification remains difficult.
| Product | Market Share (%) |
|---|---|
| Cloudera Data Platform | 8.6% |
| Palantir Foundry | 14.5% |
| Informatica Intelligent Data Management Cloud (IDMC) | 9.7% |
| Other | 67.2% |
| Product | Market Share (%) |
|---|---|
| HPE Data Fabric | 14.3% |
| Cloudera Distribution for Hadoop | 14.0% |
| Apache Spark | 13.4% |
| Other | 58.3% |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 7 |
| Large Enterprise | 26 |
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Large Enterprise | 7 |
Cloudera Data Platform offers a powerful fusion of Hadoop technology and user-centric tools, enabling seamless scalability and open-source flexibility. It supports large-scale data operations with tools like Ranger and Cloudera Data Science Workbench, offering efficient cluster management and containerization capabilities.
Designed to support extensive data needs, Cloudera Data Platform encompasses a comprehensive Hadoop stack, which includes HDFS, Hive, and Spark. Its integration with Ambari provides user-friendliness in management and configuration. Despite its strengths in scalability and security, Cloudera Data Platform requires enhancements in multi-tenant implementation, governance, and UI, while attribute-level encryption and better HDFS namenode support are also needed. Stability, especially regarding the Hue UI, financial costs, and disaster recovery are notable challenges. Additionally, integration with cloud storage and deployment methods could be more intuitive to enhance user experience, along with more effective support and community engagement.
What are the key features?Cloudera Data Platform is implemented extensively across industries like hospitality for data science activities, including managing historical data. Its adaptability extends to operational analytics for sectors like oil & gas, finance, and healthcare, often enhanced by Hortonworks Data Platform for data ingestion and analytics tasks.
Forward-leaning companies win market share because they leverage data more effectively than their competitors. Unlock the potential of your data assets with HPE Ezmeral Data Fabric (formerly MapR Data Platform). Empower your data science, analytics, and business teams by simplifying data management on a globally distributed scale. All with enterprise-grade reliability, security, and performance.
We monitor all Data Management Platforms (DMP) 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.
