Qubole Data Services and Cloudera Data Platform compete in the big data management space. While Qubole is favored for its pricing and customer service, Cloudera stands out due to its advanced features and robust security.
Features: Qubole offers auto-scaling, workload-aware scheduling, and support for various data processing frameworks. These streamline data management tasks. Cloudera provides comprehensive data lifecycle management, extensive security features including encryption, and powerful analytics capabilities, suitable for enterprises needing security and insights.
Ease of Deployment and Customer Service: Qubole is noted for straightforward deployment and a flexible cloud-native approach that allows faster onboarding. Cloudera involves more setup time because of its extensive features but offers strong customer support to assist with complex deployments.
Pricing and ROI: Qubole provides competitive pricing with a pay-as-you-go model, resulting in favorable ROI with low initial costs. Cloudera has higher upfront costs but justifies this with long-term value through scalable architecture and integrated data management, potentially leading to substantial ROI over time.
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.
A self-managing and self-optimizing data platform. Constantly analyzes and learns about your big data platform’s usage through combination of heuristics and machine learning.
Provides actionable Alerts, Insights and Recommendations (AIR) to optimize reliability, performance and costs.
Automatically enacts policies through a number of Cloud Agents to eliminate the need for repetitive manual actions
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